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Sample records for agent-based computational model

  1. Modeling civil violence: An agent-based computational approach

    PubMed Central

    Epstein, Joshua M.

    2002-01-01

    This article presents an agent-based computational model of civil violence. Two variants of the civil violence model are presented. In the first a central authority seeks to suppress decentralized rebellion. In the second a central authority seeks to suppress communal violence between two warring ethnic groups. PMID:11997450

  2. On agent-based modeling and computational social science

    PubMed Central

    Conte, Rosaria; Paolucci, Mario

    2014-01-01

    In the first part of the paper, the field of agent-based modeling (ABM) is discussed focusing on the role of generative theories, aiming at explaining phenomena by growing them. After a brief analysis of the major strengths of the field some crucial weaknesses are analyzed. In particular, the generative power of ABM is found to have been underexploited, as the pressure for simple recipes has prevailed and shadowed the application of rich cognitive models. In the second part of the paper, the renewal of interest for Computational Social Science (CSS) is focused upon, and several of its variants, such as deductive, generative, and complex CSS, are identified and described. In the concluding remarks, an interdisciplinary variant, which takes after ABM, reconciling it with the quantitative one, is proposed as a fundamental requirement for a new program of the CSS. PMID:25071642

  3. On agent-based modeling and computational social science.

    PubMed

    Conte, Rosaria; Paolucci, Mario

    2014-01-01

    In the first part of the paper, the field of agent-based modeling (ABM) is discussed focusing on the role of generative theories, aiming at explaining phenomena by growing them. After a brief analysis of the major strengths of the field some crucial weaknesses are analyzed. In particular, the generative power of ABM is found to have been underexploited, as the pressure for simple recipes has prevailed and shadowed the application of rich cognitive models. In the second part of the paper, the renewal of interest for Computational Social Science (CSS) is focused upon, and several of its variants, such as deductive, generative, and complex CSS, are identified and described. In the concluding remarks, an interdisciplinary variant, which takes after ABM, reconciling it with the quantitative one, is proposed as a fundamental requirement for a new program of the CSS.

  4. Agent-Based Computational Modeling of Cell Culture ...

    EPA Pesticide Factsheets

    Quantitative characterization of cellular dose in vitro is needed for alignment of doses in vitro and in vivo. We used the agent-based software, CompuCell3D (CC3D), to provide a stochastic description of cell growth in culture. The model was configured so that isolated cells assumed a “fried egg shape” but became increasingly cuboidal with increasing confluency. The surface area presented by each cell to the overlying medium varies from cell-to-cell and is a determinant of diffusional flux of toxicant from the medium into the cell. Thus, dose varies among cells for a given concentration of toxicant in the medium. Computer code describing diffusion of H2O2 from medium into each cell and clearance of H2O2 was calibrated against H2O2 time-course data (25, 50, or 75 uM H2O2 for 60 min) obtained with the Amplex Red assay for the medium and the H2O2-sensitive fluorescent reporter, HyPer, for cytosol. Cellular H2O2 concentrations peaked at about 5 min and were near baseline by 10 min. The model predicted a skewed distribution of surface areas, with between cell variation usually 2 fold or less. Predicted variability in cellular dose was in rough agreement with the variation in the HyPer data. These results are preliminary, as the model was not calibrated to the morphology of a specific cell type. Future work will involve morphology model calibration against human bronchial epithelial (BEAS-2B) cells. Our results show, however, the potential of agent-based modeling

  5. Agent-Based Computational Modeling of Cell Culture ...

    EPA Pesticide Factsheets

    Quantitative characterization of cellular dose in vitro is needed for alignment of doses in vitro and in vivo. We used the agent-based software, CompuCell3D (CC3D), to provide a stochastic description of cell growth in culture. The model was configured so that isolated cells assumed a “fried egg shape” but became increasingly cuboidal with increasing confluency. The surface area presented by each cell to the overlying medium varies from cell-to-cell and is a determinant of diffusional flux of toxicant from the medium into the cell. Thus, dose varies among cells for a given concentration of toxicant in the medium. Computer code describing diffusion of H2O2 from medium into each cell and clearance of H2O2 was calibrated against H2O2 time-course data (25, 50, or 75 uM H2O2 for 60 min) obtained with the Amplex Red assay for the medium and the H2O2-sensitive fluorescent reporter, HyPer, for cytosol. Cellular H2O2 concentrations peaked at about 5 min and were near baseline by 10 min. The model predicted a skewed distribution of surface areas, with between cell variation usually 2 fold or less. Predicted variability in cellular dose was in rough agreement with the variation in the HyPer data. These results are preliminary, as the model was not calibrated to the morphology of a specific cell type. Future work will involve morphology model calibration against human bronchial epithelial (BEAS-2B) cells. Our results show, however, the potential of agent-based modeling

  6. An agent-based computational model for tuberculosis spreading on age-structured populations

    NASA Astrophysics Data System (ADS)

    Graciani Rodrigues, C. C.; Espíndola, Aquino L.; Penna, T. J. P.

    2015-06-01

    In this work we present an agent-based computational model to study the spreading of the tuberculosis (TB) disease on age-structured populations. The model proposed is a merge of two previous models: an agent-based computational model for the spreading of tuberculosis and a bit-string model for biological aging. The combination of TB with the population aging, reproduces the coexistence of health states, as seen in real populations. In addition, the universal exponential behavior of mortalities curves is still preserved. Finally, the population distribution as function of age shows the prevalence of TB mostly in elders, for high efficacy treatments.

  7. Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

    ERIC Educational Resources Information Center

    Dickes, Amanda Catherine; Sengupta, Pratim

    2013-01-01

    In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these…

  8. Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

    ERIC Educational Resources Information Center

    Dickes, Amanda Catherine; Sengupta, Pratim

    2013-01-01

    In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these…

  9. High performance computing for three-dimensional agent-based molecular models.

    PubMed

    Pérez-Rodríguez, G; Pérez-Pérez, M; Fdez-Riverola, F; Lourenço, A

    2016-07-01

    Agent-based simulations are increasingly popular in exploring and understanding cellular systems, but the natural complexity of these systems and the desire to grasp different modelling levels demand cost-effective simulation strategies and tools. In this context, the present paper introduces novel sequential and distributed approaches for the three-dimensional agent-based simulation of individual molecules in cellular events. These approaches are able to describe the dimensions and position of the molecules with high accuracy and thus, study the critical effect of spatial distribution on cellular events. Moreover, two of the approaches allow multi-thread high performance simulations, distributing the three-dimensional model in a platform independent and computationally efficient way. Evaluation addressed the reproduction of molecular scenarios and different scalability aspects of agent creation and agent interaction. The three approaches simulate common biophysical and biochemical laws faithfully. The distributed approaches show improved performance when dealing with large agent populations while the sequential approach is better suited for small to medium size agent populations. Overall, the main new contribution of the approaches is the ability to simulate three-dimensional agent-based models at the molecular level with reduced implementation effort and moderate-level computational capacity. Since these approaches have a generic design, they have the major potential of being used in any event-driven agent-based tool. Copyright © 2016 Elsevier Inc. All rights reserved.

  10. Agent Based Computing Machine

    DTIC Science & Technology

    2005-12-09

    If <XY> is high, then A OR B is considered to be true. Once again, recall that A and B (and X and Y) are tokens or strings and not algebraic ...variables. There are no algebraic variables in instructions. The data and programs are inseparable as in LISP programming in the conventional computing...shows the promise of performing superior to traditional connectionist architectures for certain classes of problems that can take advantage of

  11. An agent-based computational model of the spread of tuberculosis

    NASA Astrophysics Data System (ADS)

    de Espíndola, Aquino L.; Bauch, Chris T.; Troca Cabella, Brenno C.; Souto Martinez, Alexandre

    2011-05-01

    In this work we propose an alternative model of the spread of tuberculosis (TB) and the emergence of drug resistance due to the treatment with antibiotics. We implement the simulations by an agent-based model computational approach where the spatial structure is taken into account. The spread of tuberculosis occurs according to probabilities defined by the interactions among individuals. The model was validated by reproducing results already known from the literature in which different treatment regimes yield the emergence of drug resistance. The different patterns of TB spread can be visualized at any time of the system evolution. The implementation details as well as some results of this alternative approach are discussed.

  12. The Agent-based Approach: A New Direction for Computational Models of Development.

    ERIC Educational Resources Information Center

    Schlesinger, Matthew; Parisi, Domenico

    2001-01-01

    Introduces the concepts of online and offline sampling and highlights the role of online sampling in agent-based models of learning and development. Compares the strengths of each approach for modeling particular developmental phenomena and research questions. Describes a recent agent-based model of infant causal perception. Discusses limitations…

  13. Comparing large-scale computational approaches to epidemic modeling: agent based versus structured metapopulation models

    NASA Astrophysics Data System (ADS)

    Gonçalves, Bruno; Ajelli, Marco; Balcan, Duygu; Colizza, Vittoria; Hu, Hao; Ramasco, José; Merler, Stefano; Vespignani, Alessandro

    2010-03-01

    We provide for the first time a side by side comparison of the results obtained with a stochastic agent based model and a structured metapopulation stochastic model for the evolution of a baseline pandemic event in Italy. The Agent Based model is based on the explicit representation of the Italian population through highly detailed data on the socio-demographic structure. The metapopulation simulations use the GLobal Epidemic and Mobility (GLEaM) model, based on high resolution census data worldwide, and integrating airline travel flow data with short range human mobility patterns at the global scale. Both models provide epidemic patterns that are in very good agreement at the granularity levels accessible by both approaches, with differences in peak timing of the order of few days. The age breakdown analysis shows that similar attack rates are obtained for the younger age classes.

  14. Combining Computational Fluid Dynamics and Agent-Based Modeling: a new approach to evacuation planning.

    PubMed

    Epstein, Joshua M; Pankajakshan, Ramesh; Hammond, Ross A

    2011-01-01

    We introduce a novel hybrid of two fields-Computational Fluid Dynamics (CFD) and Agent-Based Modeling (ABM)-as a powerful new technique for urban evacuation planning. CFD is a predominant technique for modeling airborne transport of contaminants, while ABM is a powerful approach for modeling social dynamics in populations of adaptive individuals. The hybrid CFD-ABM method is capable of simulating how large, spatially-distributed populations might respond to a physically realistic contaminant plume. We demonstrate the overall feasibility of CFD-ABM evacuation design, using the case of a hypothetical aerosol release in Los Angeles to explore potential effectiveness of various policy regimes. We conclude by arguing that this new approach can be powerfully applied to arbitrary population centers, offering an unprecedented preparedness and catastrophic event response tool.

  15. Computational Research on Mobile Pastoralism Using Agent-Based Modeling and Satellite Imagery

    PubMed Central

    Sakamoto, Takuto

    2016-01-01

    Dryland pastoralism has long attracted considerable attention from researchers in diverse fields. However, rigorous formal study is made difficult by the high level of mobility of pastoralists as well as by the sizable spatio-temporal variability of their environment. This article presents a new computational approach for studying mobile pastoralism that overcomes these issues. Combining multi-temporal satellite images and agent-based modeling allows a comprehensive examination of pastoral resource access over a realistic dryland landscape with unpredictable ecological dynamics. The article demonstrates the analytical potential of this approach through its application to mobile pastoralism in northeast Nigeria. Employing more than 100 satellite images of the area, extensive simulations are conducted under a wide array of circumstances, including different land-use constraints. The simulation results reveal complex dependencies of pastoral resource access on these circumstances along with persistent patterns of seasonal land use observed at the macro level. PMID:26963526

  16. Computational Research on Mobile Pastoralism Using Agent-Based Modeling and Satellite Imagery.

    PubMed

    Sakamoto, Takuto

    2016-01-01

    Dryland pastoralism has long attracted considerable attention from researchers in diverse fields. However, rigorous formal study is made difficult by the high level of mobility of pastoralists as well as by the sizable spatio-temporal variability of their environment. This article presents a new computational approach for studying mobile pastoralism that overcomes these issues. Combining multi-temporal satellite images and agent-based modeling allows a comprehensive examination of pastoral resource access over a realistic dryland landscape with unpredictable ecological dynamics. The article demonstrates the analytical potential of this approach through its application to mobile pastoralism in northeast Nigeria. Employing more than 100 satellite images of the area, extensive simulations are conducted under a wide array of circumstances, including different land-use constraints. The simulation results reveal complex dependencies of pastoral resource access on these circumstances along with persistent patterns of seasonal land use observed at the macro level.

  17. Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

    NASA Astrophysics Data System (ADS)

    Dickes, Amanda Catherine; Sengupta, Pratim

    2013-06-01

    In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these agents obey simple rules assigned or manipulated by the user (e.g., speeding up, slowing down, etc.). It is the interactions between these agents, based on the rules assigned by the user, that give rise to emergent, aggregate-level behavior (e.g., formation and movement of the traffic jam). Natural selection is such an emergent phenomenon, which has been shown to be challenging for novices (K16 students) to understand. Whereas prior research on learning evolutionary phenomena with MABMs has typically focused on high school students and beyond, we investigate how elementary students (4th graders) develop multi-level explanations of some introductory aspects of natural selection—species differentiation and population change—through scaffolded interactions with an MABM that simulates predator-prey dynamics in a simple birds-butterflies ecosystem. We conducted a semi-clinical interview based study with ten participants, in which we focused on the following: a) identifying the nature of learners' initial interpretations of salient events or elements of the represented phenomena, b) identifying the roles these interpretations play in the development of their multi-level explanations, and c) how attending to different levels of the relevant phenomena can make explicit different mechanisms to the learners. In addition, our analysis also shows that although there were differences between high- and low-performing students (in terms of being able to explain population-level behaviors) in the pre-test, these differences disappeared in the post-test.

  18. Understanding the Melanocyte Distribution in Human Epidermis: An Agent-Based Computational Model Approach

    PubMed Central

    Thingnes, Josef; Lavelle, Timothy J.; Hovig, Eivind; Omholt, Stig W.

    2012-01-01

    The strikingly even color of human skin is maintained by the uniform distribution of melanocytes among keratinocytes in the basal layer of the human epidermis. In this work, we investigated three possible hypotheses on the mechanism by which the melanocytes and keratinocytes organize themselves to generate this pattern. We let the melanocyte migration be aided by (1) negative chemotaxis due to a substance produced by the melanocytes themselves, or (2) positive chemotaxis due to a substance produced by keratinocytes lacking direct physical contact with a melanocyte, or (3) positive chemotaxis due to a substance produced by keratinocytes in a distance-to-melanocytes dependent manner. The three hypotheses were implemented in an agent-based computational model of cellular interactions in the basal layer of the human epidermis. We found that they generate mutually exclusive predictions that can be tested by existing experimental protocols. This model forms a basis for further understanding of the communication between melanocytes and other skin cells in skin homeostasis. PMID:22792296

  19. An Advanced Computational Approach to System of Systems Analysis & Architecting Using Agent-Based Behavioral Model

    DTIC Science & Technology

    2012-09-30

    The Wave Process Model provides a framework for an agent-based modeling methodology, which is used to abstract the non- utopian behavioral aspects...that SoS participants exhibit nominal behavior ( utopian behavior), but deviation from nominal motivation leads to complications and disturbances in... characteristics . Figure 2 outlines the agent architecture components and flow of information among components. Own Process Control (OPC) Cooperation

  20. Agent-based computational model investigates muscle-specific responses to disuse-induced atrophy

    PubMed Central

    Martin, Kyle S.; Peirce, Shayn M.

    2015-01-01

    Skeletal muscle is highly responsive to use. In particular, muscle atrophy attributable to decreased activity is a common problem among the elderly and injured/immobile. However, each muscle does not respond the same way. We developed an agent-based model that generates a tissue-level skeletal muscle response to disuse/immobilization. The model incorporates tissue-specific muscle fiber architecture parameters and simulates changes in muscle fiber size as a result of disuse-induced atrophy that are consistent with published experiments. We created simulations of 49 forelimb and hindlimb muscles of the rat by incorporating eight fiber-type and size parameters to explore how these parameters, which vary widely across muscles, influence sensitivity to disuse-induced atrophy. Of the 49 muscles modeled, the soleus exhibited the greatest atrophy after 14 days of simulated immobilization (51% decrease in fiber size), whereas the extensor digitorum communis atrophied the least (32%). Analysis of these simulations revealed that both fiber-type distribution and fiber-size distribution influence the sensitivity to disuse atrophy even though no single tissue architecture parameter correlated with atrophy rate. Additionally, software agents representing fibroblasts were incorporated into the model to investigate cellular interactions during atrophy. Sensitivity analyses revealed that fibroblast agents have the potential to affect disuse-induced atrophy, albeit with a lesser effect than fiber type and size. In particular, muscle atrophy elevated slightly with increased initial fibroblast population and increased production of TNF-α. Overall, the agent-based model provides a novel framework for investigating both tissue adaptations and cellular interactions in skeletal muscle during atrophy. PMID:25722379

  1. Agent-based computational model investigates muscle-specific responses to disuse-induced atrophy.

    PubMed

    Martin, Kyle S; Blemker, Silvia S; Peirce, Shayn M

    2015-05-15

    Skeletal muscle is highly responsive to use. In particular, muscle atrophy attributable to decreased activity is a common problem among the elderly and injured/immobile. However, each muscle does not respond the same way. We developed an agent-based model that generates a tissue-level skeletal muscle response to disuse/immobilization. The model incorporates tissue-specific muscle fiber architecture parameters and simulates changes in muscle fiber size as a result of disuse-induced atrophy that are consistent with published experiments. We created simulations of 49 forelimb and hindlimb muscles of the rat by incorporating eight fiber-type and size parameters to explore how these parameters, which vary widely across muscles, influence sensitivity to disuse-induced atrophy. Of the 49 muscles modeled, the soleus exhibited the greatest atrophy after 14 days of simulated immobilization (51% decrease in fiber size), whereas the extensor digitorum communis atrophied the least (32%). Analysis of these simulations revealed that both fiber-type distribution and fiber-size distribution influence the sensitivity to disuse atrophy even though no single tissue architecture parameter correlated with atrophy rate. Additionally, software agents representing fibroblasts were incorporated into the model to investigate cellular interactions during atrophy. Sensitivity analyses revealed that fibroblast agents have the potential to affect disuse-induced atrophy, albeit with a lesser effect than fiber type and size. In particular, muscle atrophy elevated slightly with increased initial fibroblast population and increased production of TNF-α. Overall, the agent-based model provides a novel framework for investigating both tissue adaptations and cellular interactions in skeletal muscle during atrophy. Copyright © 2015 the American Physiological Society.

  2. From Agents to Continuous Change via Aesthetics: Learning Mechanics with Visual Agent-Based Computational Modeling

    ERIC Educational Resources Information Center

    Sengupta, Pratim; Farris, Amy Voss; Wright, Mason

    2012-01-01

    Novice learners find motion as a continuous process of change challenging to understand. In this paper, we present a pedagogical approach based on agent-based, visual programming to address this issue. Integrating agent-based programming, in particular, Logo programming, with curricular science has been shown to be challenging in previous research…

  3. From Agents to Continuous Change via Aesthetics: Learning Mechanics with Visual Agent-Based Computational Modeling

    ERIC Educational Resources Information Center

    Sengupta, Pratim; Farris, Amy Voss; Wright, Mason

    2012-01-01

    Novice learners find motion as a continuous process of change challenging to understand. In this paper, we present a pedagogical approach based on agent-based, visual programming to address this issue. Integrating agent-based programming, in particular, Logo programming, with curricular science has been shown to be challenging in previous research…

  4. An agent based model of genotype editing

    SciTech Connect

    Rocha, L. M.; Huang, C. F.

    2004-01-01

    This paper presents our investigation on an agent-based model of Genotype Editing. This model is based on several characteristics that are gleaned from the RNA editing system as observed in several organisms. The incorporation of editing mechanisms in an evolutionary agent-based model provides a means for evolving agents with heterogenous post-transcriptional processes. The study of this agent-based genotype-editing model has shed some light into the evolutionary implications of RNA editing as well as established an advantageous evolutionary computation algorithm for machine learning. We expect that our proposed model may both facilitate determining the evolutionary role of RNA editing in biology, and advance the current state of research in agent-based optimization.

  5. A Comparison of Computational Cognitive Models: Agent-Based Systems Versus Rule-Based Architectures

    DTIC Science & Technology

    2003-03-01

    called Rational Choice Theory (Zsambok, 1997). The decision maker generates a list of several possible actions, and then chooses the best action...from the list. The transition from the descriptive rational choice theory model to a computational model is relatively straightforward. The problem...given goal state. While rational choice theory may be applicable in many environments, recent studies of experienced decision makers in more complex

  6. Geometry of behavioral spaces: A computational approach to analysis and understanding of agent based models and agent behaviors

    NASA Astrophysics Data System (ADS)

    Cenek, Martin; Dahl, Spencer K.

    2016-11-01

    Systems with non-linear dynamics frequently exhibit emergent system behavior, which is important to find and specify rigorously to understand the nature of the modeled phenomena. Through this analysis, it is possible to characterize phenomena such as how systems assemble or dissipate and what behaviors lead to specific final system configurations. Agent Based Modeling (ABM) is one of the modeling techniques used to study the interaction dynamics between a system's agents and its environment. Although the methodology of ABM construction is well understood and practiced, there are no computational, statistically rigorous, comprehensive tools to evaluate an ABM's execution. Often, a human has to observe an ABM's execution in order to analyze how the ABM functions, identify the emergent processes in the agent's behavior, or study a parameter's effect on the system-wide behavior. This paper introduces a new statistically based framework to automatically analyze agents' behavior, identify common system-wide patterns, and record the probability of agents changing their behavior from one pattern of behavior to another. We use network based techniques to analyze the landscape of common behaviors in an ABM's execution. Finally, we test the proposed framework with a series of experiments featuring increasingly emergent behavior. The proposed framework will allow computational comparison of ABM executions, exploration of a model's parameter configuration space, and identification of the behavioral building blocks in a model's dynamics.

  7. An Advanced Computational Approach to System of Systems Analysis & Architecting Using Agent-Based Behavioral Model

    DTIC Science & Technology

    2013-03-29

    Opportunistic - Markov Chain Model ................................................................................. 75 4 ABM Integration Framework and...round 2 of negotiation 3.5.4 Opportunistic - Markov Chain Model The model presented here for the system in question is an “opportunistic” model, i.e...funding it will need  The deadline by which it will be able to complete its task A project management model based on Markov chains will be used for

  8. Agent-based modelling in synthetic biology

    PubMed Central

    2016-01-01

    Biological systems exhibit complex behaviours that emerge at many different levels of organization. These span the regulation of gene expression within single cells to the use of quorum sensing to co-ordinate the action of entire bacterial colonies. Synthetic biology aims to make the engineering of biology easier, offering an opportunity to control natural systems and develop new synthetic systems with useful prescribed behaviours. However, in many cases, it is not understood how individual cells should be programmed to ensure the emergence of a required collective behaviour. Agent-based modelling aims to tackle this problem, offering a framework in which to simulate such systems and explore cellular design rules. In this article, I review the use of agent-based models in synthetic biology, outline the available computational tools, and provide details on recently engineered biological systems that are amenable to this approach. I further highlight the challenges facing this methodology and some of the potential future directions. PMID:27903820

  9. Agent Based Modeling Applications for Geosciences

    NASA Astrophysics Data System (ADS)

    Stein, J. S.

    2004-12-01

    Agent-based modeling techniques have successfully been applied to systems in which complex behaviors or outcomes arise from varied interactions between individuals in the system. Each individual interacts with its environment, as well as with other individuals, by following a set of relatively simple rules. Traditionally this "bottom-up" modeling approach has been applied to problems in the fields of economics and sociology, but more recently has been introduced to various disciplines in the geosciences. This technique can help explain the origin of complex processes from a relatively simple set of rules, incorporate large and detailed datasets when they exist, and simulate the effects of extreme events on system-wide behavior. Some of the challenges associated with this modeling method include: significant computational requirements in order to keep track of thousands to millions of agents, methods and strategies of model validation are lacking, as is a formal methodology for evaluating model uncertainty. Challenges specific to the geosciences, include how to define agents that control water, contaminant fluxes, climate forcing and other physical processes and how to link these "geo-agents" into larger agent-based simulations that include social systems such as demographics economics and regulations. Effective management of limited natural resources (such as water, hydrocarbons, or land) requires an understanding of what factors influence the demand for these resources on a regional and temporal scale. Agent-based models can be used to simulate this demand across a variety of sectors under a range of conditions and determine effective and robust management policies and monitoring strategies. The recent focus on the role of biological processes in the geosciences is another example of an area that could benefit from agent-based applications. A typical approach to modeling the effect of biological processes in geologic media has been to represent these processes in

  10. Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach

    PubMed Central

    2016-01-01

    Background Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. Purpose It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. Method We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. Results The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach. PMID:26812235

  11. Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach.

    PubMed

    Laghari, Samreen; Niazi, Muaz A

    2016-01-01

    Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.

  12. An Advanced Computational Approach to System of Systems Analysis & Architecting Using Agent-Based Behavioral Model: Phase 2

    DTIC Science & Technology

    2013-11-18

    CONTRACT NUMBER H98230-08-D-0171 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Dagli /Dr. Cihan 5d. PROJECT NUMBER RT 44-6 5e. TASK...SoS, and can be applied early in the life cycle when there is uncertainty and ambiguity about SoS requirements, architecture, DoD Acquisition guidance...autonomous robots [7]. Agent-based modeling methodology is used to abstract behavioral aspects of the acquisition process. In this project , the

  13. Agent-based modelling in synthetic biology.

    PubMed

    Gorochowski, Thomas E

    2016-11-30

    Biological systems exhibit complex behaviours that emerge at many different levels of organization. These span the regulation of gene expression within single cells to the use of quorum sensing to co-ordinate the action of entire bacterial colonies. Synthetic biology aims to make the engineering of biology easier, offering an opportunity to control natural systems and develop new synthetic systems with useful prescribed behaviours. However, in many cases, it is not understood how individual cells should be programmed to ensure the emergence of a required collective behaviour. Agent-based modelling aims to tackle this problem, offering a framework in which to simulate such systems and explore cellular design rules. In this article, I review the use of agent-based models in synthetic biology, outline the available computational tools, and provide details on recently engineered biological systems that are amenable to this approach. I further highlight the challenges facing this methodology and some of the potential future directions. © 2016 The Author(s).

  14. Agent-Based Service Composition in Cloud Computing

    NASA Astrophysics Data System (ADS)

    Gutierrez-Garcia, J. Octavio; Sim, Kwang-Mong

    In a Cloud-computing environment, consumers, brokers, and service providers interact to achieve their individual purposes. In this regard, service providers offer a pool of resources wrapped as web services, which should be composed by broker agents to provide a single virtualized service to Cloud consumers. In this study, an agent-based test bed for simulating Cloud-computing environments is developed. Each Cloud participant is represented by an agent, whose behavior is defined by means of colored Petri nets. The relationship between web services and service providers is modeled using object Petri nets. Both Petri net formalisms are combined to support a design methodology for defining concurrent and parallel service choreographies. This results in the creation of a dynamic agent-based service composition algorithm. The simulation results indicate that service composition is achieved with a linear time complexity despite dealing with interleaving choreographies and synchronization of heterogeneous services.

  15. AGENT-BASED MODELS IN EMPIRICAL SOCIAL RESEARCH*

    PubMed Central

    Bruch, Elizabeth; Atwell, Jon

    2014-01-01

    Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first discuss the motivations for using agent-based models in both basic science and policy-oriented social research. Next, we provide an overview of methods and strategies for incorporating data on behavior and populations into agent-based models, and review techniques for validating and testing the sensitivity of agent-based models. We close with suggested directions for future research. PMID:25983351

  16. Multiscale agent-based consumer market modeling.

    SciTech Connect

    North, M. J.; Macal, C. M.; St. Aubin, J.; Thimmapuram, P.; Bragen, M.; Hahn, J.; Karr, J.; Brigham, N.; Lacy, M. E.; Hampton, D.; Decision and Information Sciences; Procter & Gamble Co.

    2010-05-01

    Consumer markets have been studied in great depth, and many techniques have been used to represent them. These have included regression-based models, logit models, and theoretical market-level models, such as the NBD-Dirichlet approach. Although many important contributions and insights have resulted from studies that relied on these models, there is still a need for a model that could more holistically represent the interdependencies of the decisions made by consumers, retailers, and manufacturers. When the need is for a model that could be used repeatedly over time to support decisions in an industrial setting, it is particularly critical. Although some existing methods can, in principle, represent such complex interdependencies, their capabilities might be outstripped if they had to be used for industrial applications, because of the details this type of modeling requires. However, a complementary method - agent-based modeling - shows promise for addressing these issues. Agent-based models use business-driven rules for individuals (e.g., individual consumer rules for buying items, individual retailer rules for stocking items, or individual firm rules for advertizing items) to determine holistic, system-level outcomes (e.g., to determine if brand X's market share is increasing). We applied agent-based modeling to develop a multi-scale consumer market model. We then conducted calibration, verification, and validation tests of this model. The model was successfully applied by Procter & Gamble to several challenging business problems. In these situations, it directly influenced managerial decision making and produced substantial cost savings.

  17. A hybrid agent-based approach for modeling microbiological systems.

    PubMed

    Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

    2008-11-21

    Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

  18. Agent-Based Modeling in Systems Pharmacology.

    PubMed

    Cosgrove, J; Butler, J; Alden, K; Read, M; Kumar, V; Cucurull-Sanchez, L; Timmis, J; Coles, M

    2015-11-01

    Modeling and simulation (M&S) techniques provide a platform for knowledge integration and hypothesis testing to gain insights into biological systems that would not be possible a priori. Agent-based modeling (ABM) is an M&S technique that focuses on describing individual components rather than homogenous populations. This tutorial introduces ABM to systems pharmacologists, using relevant case studies to highlight how ABM-specific strengths have yielded success in the area of preclinical mechanistic modeling.

  19. Computational Scientific Inquiry with Virtual Worlds and Agent-Based Models: New Ways of Doing Science to Learn Science

    ERIC Educational Resources Information Center

    Jacobson, Michael J.; Taylor, Charlotte E.; Richards, Deborah

    2016-01-01

    In this paper, we propose computational scientific inquiry (CSI) as an innovative model for learning important scientific knowledge and new practices for "doing" science. This approach involves the use of a "game-like" virtual world for students to experience virtual biological fieldwork in conjunction with using an agent-based…

  20. Computational Scientific Inquiry with Virtual Worlds and Agent-Based Models: New Ways of Doing Science to Learn Science

    ERIC Educational Resources Information Center

    Jacobson, Michael J.; Taylor, Charlotte E.; Richards, Deborah

    2016-01-01

    In this paper, we propose computational scientific inquiry (CSI) as an innovative model for learning important scientific knowledge and new practices for "doing" science. This approach involves the use of a "game-like" virtual world for students to experience virtual biological fieldwork in conjunction with using an agent-based…

  1. Agent-Based Models in Empirical Social Research

    ERIC Educational Resources Information Center

    Bruch, Elizabeth; Atwell, Jon

    2015-01-01

    Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first…

  2. Thread Group Multithreading: Accelerating the Computation of an Agent-Based Power System Modeling and Simulation Tool -- C GridLAB-D

    SciTech Connect

    Jin, Shuangshuang; Chassin, David P.

    2014-01-06

    GridLAB-DTM is an open source next generation agent-based smart-grid simulator that provides unprecedented capability to model the performance of smart grid technologies. Over the past few years, GridLAB-D has been used to conduct important analyses of smart grid concepts, but it is still quite limited by its computational performance. In order to break through the performance bottleneck to meet the need for large scale power grid simulations, we develop a thread group mechanism to implement highly granular multithreaded computation in GridLAB-D. We achieve close to linear speedups on multithreading version compared against the single-thread version of the same code running on general purpose multi-core commodity for a benchmark simple house model. The performance of the multithreading code shows favorable scalability properties and resource utilization, and much shorter execution time for large-scale power grid simulations.

  3. Agent-based modeling: case study in cleavage furrow models.

    PubMed

    Mogilner, Alex; Manhart, Angelika

    2016-11-07

    The number of studies in cell biology in which quantitative models accompany experiments has been growing steadily. Roughly, mathematical and computational techniques of these models can be classified as "differential equation based" (DE) or "agent based" (AB). Recently AB models have started to outnumber DE models, but understanding of AB philosophy and methodology is much less widespread than familiarity with DE techniques. Here we use the history of modeling a fundamental biological problem-positioning of the cleavage furrow in dividing cells-to explain how and why DE and AB models are used. We discuss differences, advantages, and shortcomings of these two approaches.

  4. Tutorial on agent-based modeling and simulation.

    SciTech Connect

    Macal, C. M.; North, M. J.; Decision and Information Sciences

    2005-01-01

    Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. ABMS promises to have far-reaching effects on the way that businesses use computers to support decision-making and researchers use electronic laboratories to support their research. Some have gone so far as to contend that ABMS is a third way of doing science besides deductive and inductive reasoning. Computational advances have made possible a growing number of agent-based applications in a variety of fields. Applications range from modeling agent behavior in the stock market and supply chains, to predicting the spread of epidemics and the threat of bio-warfare, from modeling consumer behavior to understanding the fall of ancient civilizations, to name a few. This tutorial describes the theoretical and practical foundations of ABMS, identifies toolkits and methods for developing ABMS models, and provides some thoughts on the relationship between ABMS and traditional modeling techniques.

  5. Simulating cancer growth with multiscale agent-based modeling.

    PubMed

    Wang, Zhihui; Butner, Joseph D; Kerketta, Romica; Cristini, Vittorio; Deisboeck, Thomas S

    2015-02-01

    There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models.

  6. Agent Based Modeling as an Educational Tool

    NASA Astrophysics Data System (ADS)

    Fuller, J. H.; Johnson, R.; Castillo, V.

    2012-12-01

    Motivation is a key element in high school education. One way to improve motivation and provide content, while helping address critical thinking and problem solving skills, is to have students build and study agent based models in the classroom. This activity visually connects concepts with their applied mathematical representation. "Engaging students in constructing models may provide a bridge between frequently disconnected conceptual and mathematical forms of knowledge." (Levy and Wilensky, 2011) We wanted to discover the feasibility of implementing a model based curriculum in the classroom given current and anticipated core and content standards.; Simulation using California GIS data ; Simulation of high school student lunch popularity using aerial photograph on top of terrain value map.

  7. Adding ecosystem function to agent-based land use models

    PubMed Central

    Yadav, V.; Del Grosso, S.J.; Parton, W.J.; Malanson, G.P.

    2015-01-01

    The objective of this paper is to examine issues in the inclusion of simulations of ecosystem functions in agent-based models of land use decision-making. The reasons for incorporating these simulations include local interests in land fertility and global interests in carbon sequestration. Biogeochemical models are needed in order to calculate such fluxes. The Century model is described with particular attention to the land use choices that it can encompass. When Century is applied to a land use problem the combinatorial choices lead to a potentially unmanageable number of simulation runs. Century is also parameter-intensive. Three ways of including Century output in agent-based models, ranging from separately calculated look-up tables to agents running Century within the simulation, are presented. The latter may be most efficient, but it moves the computing costs to where they are most problematic. Concern for computing costs should not be a roadblock. PMID:26191077

  8. Agent based modeling in tactical wargaming

    NASA Astrophysics Data System (ADS)

    James, Alex; Hanratty, Timothy P.; Tuttle, Daniel C.; Coles, John B.

    2016-05-01

    Army staffs at division, brigade, and battalion levels often plan for contingency operations. As such, analysts consider the impact and potential consequences of actions taken. The Army Military Decision-Making Process (MDMP) dictates identification and evaluation of possible enemy courses of action; however, non-state actors often do not exhibit the same level and consistency of planned actions that the MDMP was originally designed to anticipate. The fourth MDMP step is a particular challenge, wargaming courses of action within the context of complex social-cultural behaviors. Agent-based Modeling (ABM) and its resulting emergent behavior is a potential solution to model terrain in terms of the human domain and improve the results and rigor of the traditional wargaming process.

  9. A technology path to tactical agent-based modeling

    NASA Astrophysics Data System (ADS)

    James, Alex; Hanratty, Timothy P.

    2017-05-01

    Wargaming is a process of thinking through and visualizing events that could occur during a possible course of action. Over the past 200 years, wargaming has matured into a set of formalized processes. One area of growing interest is the application of agent-based modeling. Agent-based modeling and its additional supporting technologies has potential to introduce a third-generation wargaming capability to the Army, creating a positive overmatch decision-making capability. In its simplest form, agent-based modeling is a computational technique that helps the modeler understand and simulate how the "whole of a system" responds to change over time. It provides a decentralized method of looking at situations where individual agents are instantiated within an environment, interact with each other, and empowered to make their own decisions. However, this technology is not without its own risks and limitations. This paper explores a technology roadmap, identifying research topics that could realize agent-based modeling within a tactical wargaming context.

  10. Agent Based Model of Livestock Movements

    NASA Astrophysics Data System (ADS)

    Miron, D. J.; Emelyanova, I. V.; Donald, G. E.; Garner, G. M.

    The modelling of livestock movements within Australia is of national importance for the purposes of the management and control of exotic disease spread, infrastructure development and the economic forecasting of livestock markets. In this paper an agent based model for the forecasting of livestock movements is presented. This models livestock movements from farm to farm through a saleyard. The decision of farmers to sell or buy cattle is often complex and involves many factors such as climate forecast, commodity prices, the type of farm enterprise, the number of animals available and associated off-shore effects. In this model the farm agent's intelligence is implemented using a fuzzy decision tree that utilises two of these factors. These two factors are the livestock price fetched at the last sale and the number of stock on the farm. On each iteration of the model farms choose either to buy, sell or abstain from the market thus creating an artificial supply and demand. The buyers and sellers then congregate at the saleyard where livestock are auctioned using a second price sealed bid. The price time series output by the model exhibits properties similar to those found in real livestock markets.

  11. Agent-based modeling in ecological economics.

    PubMed

    Heckbert, Scott; Baynes, Tim; Reeson, Andrew

    2010-01-01

    Interconnected social and environmental systems are the domain of ecological economics, and models can be used to explore feedbacks and adaptations inherent in these systems. Agent-based modeling (ABM) represents autonomous entities, each with dynamic behavior and heterogeneous characteristics. Agents interact with each other and their environment, resulting in emergent outcomes at the macroscale that can be used to quantitatively analyze complex systems. ABM is contributing to research questions in ecological economics in the areas of natural resource management and land-use change, urban systems modeling, market dynamics, changes in consumer attitudes, innovation, and diffusion of technology and management practices, commons dilemmas and self-governance, and psychological aspects to human decision making and behavior change. Frontiers for ABM research in ecological economics involve advancing the empirical calibration and validation of models through mixed methods, including surveys, interviews, participatory modeling, and, notably, experimental economics to test specific decision-making hypotheses. Linking ABM with other modeling techniques at the level of emergent properties will further advance efforts to understand dynamics of social-environmental systems.

  12. Agent-based modeling and simulation Part 3 : desktop ABMS.

    SciTech Connect

    Macal, C. M.; North, M. J.; Decision and Information Sciences

    2007-01-01

    Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. ABMS promises to have far-reaching effects on the way that businesses use computers to support decision-making and researchers use electronic laboratories to support their research. Some have gone so far as to contend that ABMS 'is a third way of doing science,' in addition to traditional deductive and inductive reasoning (Axelrod 1997b). Computational advances have made possible a growing number of agent-based models across a variety of application domains. Applications range from modeling agent behavior in the stock market, supply chains, and consumer markets, to predicting the spread of epidemics, the threat of bio-warfare, and the factors responsible for the fall of ancient civilizations. This tutorial describes the theoretical and practical foundations of ABMS, identifies toolkits and methods for developing agent models, and illustrates the development of a simple agent-based model of shopper behavior using spreadsheets.

  13. Agent-based models in translational systems biology

    PubMed Central

    An, Gary; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram

    2013-01-01

    Effective translational methodologies for knowledge representation are needed in order to make strides against the constellation of diseases that affect the world today. These diseases are defined by their mechanistic complexity, redundancy, and nonlinearity. Translational systems biology aims to harness the power of computational simulation to streamline drug/device design, simulate clinical trials, and eventually to predict the effects of drugs on individuals. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggests that this modeling framework is well suited for translational systems biology. This review describes agent-based modeling and gives examples of its translational applications in the context of acute inflammation and wound healing. PMID:20835989

  14. Sepsis reconsidered: Identifying novel metrics for behavioral landscape characterization with a high-performance computing implementation of an agent-based model.

    PubMed

    Cockrell, Chase; An, Gary

    2017-10-07

    Sepsis affects nearly 1 million people in the United States per year, has a mortality rate of 28-50% and requires more than $20 billion a year in hospital costs. Over a quarter century of research has not yielded a single reliable diagnostic test or a directed therapeutic agent for sepsis. Central to this insufficiency is the fact that sepsis remains a clinical/physiological diagnosis representing a multitude of molecularly heterogeneous pathological trajectories. Advances in computational capabilities offered by High Performance Computing (HPC) platforms call for an evolution in the investigation of sepsis to attempt to define the boundaries of traditional research (bench, clinical and computational) through the use of computational proxy models. We present a novel investigatory and analytical approach, derived from how HPC resources and simulation are used in the physical sciences, to identify the epistemic boundary conditions of the study of clinical sepsis via the use of a proxy agent-based model of systemic inflammation. Current predictive models for sepsis use correlative methods that are limited by patient heterogeneity and data sparseness. We address this issue by using an HPC version of a system-level validated agent-based model of sepsis, the Innate Immune Response ABM (IIRBM), as a proxy system in order to identify boundary conditions for the possible behavioral space for sepsis. We then apply advanced analysis derived from the study of Random Dynamical Systems (RDS) to identify novel means for characterizing system behavior and providing insight into the tractability of traditional investigatory methods. The behavior space of the IIRABM was examined by simulating over 70 million sepsis patients for up to 90 days in a sweep across the following parameters: cardio-respiratory-metabolic resilience; microbial invasiveness; microbial toxigenesis; and degree of nosocomial exposure. In addition to using established methods for describing parameter space, we

  15. Validating agent based models through virtual worlds.

    SciTech Connect

    Lakkaraju, Kiran; Whetzel, Jonathan H.; Lee, Jina; Bier, Asmeret Brooke; Cardona-Rivera, Rogelio E.; Bernstein, Jeremy Ray Rhythm

    2014-01-01

    As the US continues its vigilance against distributed, embedded threats, understanding the political and social structure of these groups becomes paramount for predicting and dis- rupting their attacks. Agent-based models (ABMs) serve as a powerful tool to study these groups. While the popularity of social network tools (e.g., Facebook, Twitter) has provided extensive communication data, there is a lack of ne-grained behavioral data with which to inform and validate existing ABMs. Virtual worlds, in particular massively multiplayer online games (MMOG), where large numbers of people interact within a complex environ- ment for long periods of time provide an alternative source of data. These environments provide a rich social environment where players engage in a variety of activities observed between real-world groups: collaborating and/or competing with other groups, conducting battles for scarce resources, and trading in a market economy. Strategies employed by player groups surprisingly re ect those seen in present-day con icts, where players use diplomacy or espionage as their means for accomplishing their goals. In this project, we propose to address the need for ne-grained behavioral data by acquiring and analyzing game data a commercial MMOG, referred to within this report as Game X. The goals of this research were: (1) devising toolsets for analyzing virtual world data to better inform the rules that govern a social ABM and (2) exploring how virtual worlds could serve as a source of data to validate ABMs established for analogous real-world phenomena. During this research, we studied certain patterns of group behavior to compliment social modeling e orts where a signi cant lack of detailed examples of observed phenomena exists. This report outlines our work examining group behaviors that underly what we have termed the Expression-To-Action (E2A) problem: determining the changes in social contact that lead individuals/groups to engage in a particular behavior

  16. Agent-Based Computational Modeling of Cell Culture: Understanding Dosimetry In Vitro as Part of In Vitro to In Vivo Extrapolation

    EPA Science Inventory

    Quantitative characterization of cellular dose in vitro is needed for alignment of doses in vitro and in vivo. We used the agent-based software, CompuCell3D (CC3D), to provide a stochastic description of cell growth in culture. The model was configured so that isolated cells assu...

  17. Agent-Based Computational Modeling of Cell Culture: Understanding Dosimetry In Vitro as Part of In Vitro to In Vivo Extrapolation

    EPA Science Inventory

    Quantitative characterization of cellular dose in vitro is needed for alignment of doses in vitro and in vivo. We used the agent-based software, CompuCell3D (CC3D), to provide a stochastic description of cell growth in culture. The model was configured so that isolated cells assu...

  18. Exploring Tradeoffs in Demand-side and Supply-side Management of Urban Water Resources using Agent-based Modeling and Evolutionary Computation

    NASA Astrophysics Data System (ADS)

    Kanta, L.; Berglund, E. Z.

    2015-12-01

    Urban water supply systems may be managed through supply-side and demand-side strategies, which focus on water source expansion and demand reductions, respectively. Supply-side strategies bear infrastructure and energy costs, while demand-side strategies bear costs of implementation and inconvenience to consumers. To evaluate the performance of demand-side strategies, the participation and water use adaptations of consumers should be simulated. In this study, a Complex Adaptive Systems (CAS) framework is developed to simulate consumer agents that change their consumption to affect the withdrawal from the water supply system, which, in turn influences operational policies and long-term resource planning. Agent-based models are encoded to represent consumers and a policy maker agent and are coupled with water resources system simulation models. The CAS framework is coupled with an evolutionary computation-based multi-objective methodology to explore tradeoffs in cost, inconvenience to consumers, and environmental impacts for both supply-side and demand-side strategies. Decisions are identified to specify storage levels in a reservoir that trigger (1) increases in the volume of water pumped through inter-basin transfers from an external reservoir and (2) drought stages, which restrict the volume of water that is allowed for residential outdoor uses. The proposed methodology is demonstrated for Arlington, Texas, water supply system to identify non-dominated strategies for an historic drought decade. Results demonstrate that pumping costs associated with maximizing environmental reliability exceed pumping costs associated with minimizing restrictions on consumer water use.

  19. Agent-based models of financial markets

    NASA Astrophysics Data System (ADS)

    Samanidou, E.; Zschischang, E.; Stauffer, D.; Lux, T.

    2007-03-01

    This review deals with several microscopic ('agent-based') models of financial markets which have been studied by economists and physicists over the last decade: Kim-Markowitz, Levy-Levy-Solomon, Cont-Bouchaud, Solomon-Weisbuch, Lux-Marchesi, Donangelo-Sneppen and Solomon-Levy-Huang. After an overview of simulation approaches in financial economics, we first give a summary of the Donangelo-Sneppen model of monetary exchange and compare it with related models in economics literature. Our selective review then outlines the main ingredients of some influential early models of multi-agent dynamics in financial markets (Kim-Markowitz, Levy-Levy-Solomon). As will be seen, these contributions draw their inspiration from the complex appearance of investors' interactions in real-life markets. Their main aim is to reproduce (and, thereby, provide possible explanations) for the spectacular bubbles and crashes seen in certain historical episodes, but they lack (like almost all the work before 1998 or so) a perspective in terms of the universal statistical features of financial time series. In fact, awareness of a set of such regularities (power-law tails of the distribution of returns, temporal scaling of volatility) only gradually appeared over the nineties. With the more precise description of the formerly relatively vague characteristics (e.g. moving from the notion of fat tails to the more concrete one of a power law with index around three), it became clear that financial market dynamics give rise to some kind of universal scaling law. Showing similarities with scaling laws for other systems with many interacting sub-units, an exploration of financial markets as multi-agent systems appeared to be a natural consequence. This topic has been pursued by quite a number of contributions appearing in both the physics and economics literature since the late nineties. From the wealth of different flavours of multi-agent models that have appeared up to now, we discuss the Cont

  20. An Agent-Based Model of a Hepatic Inflammatory Response to Salmonella: A Computational Study under a Large Set of Experimental Data

    PubMed Central

    Chapes, Stephen K.; Ben-Arieh, David; Wu, Chih-Hang

    2016-01-01

    We present an agent-based model (ABM) to simulate a hepatic inflammatory response (HIR) in a mouse infected by Salmonella that sometimes progressed to problematic proportions, known as “sepsis”. Based on over 200 published studies, this ABM describes interactions among 21 cells or cytokines and incorporates 226 experimental data sets and/or data estimates from those reports to simulate a mouse HIR in silico. Our simulated results reproduced dynamic patterns of HIR reported in the literature. As shown in vivo, our model also demonstrated that sepsis was highly related to the initial Salmonella dose and the presence of components of the adaptive immune system. We determined that high mobility group box-1, C-reactive protein, and the interleukin-10: tumor necrosis factor-α ratio, and CD4+ T cell: CD8+ T cell ratio, all recognized as biomarkers during HIR, significantly correlated with outcomes of HIR. During therapy-directed silico simulations, our results demonstrated that anti-agent intervention impacted the survival rates of septic individuals in a time-dependent manner. By specifying the infected species, source of infection, and site of infection, this ABM enabled us to reproduce the kinetics of several essential indicators during a HIR, observe distinct dynamic patterns that are manifested during HIR, and allowed us to test proposed therapy-directed treatments. Although limitation still exists, this ABM is a step forward because it links underlying biological processes to computational simulation and was validated through a series of comparisons between the simulated results and experimental studies. PMID:27556404

  1. Who's your neighbor? neighbor identification for agent-based modeling.

    SciTech Connect

    Macal, C. M.; Howe, T. R.; Decision and Information Sciences; Univ. of Chicago

    2006-01-01

    Agent-based modeling and simulation, based on the cellular automata paradigm, is an approach to modeling complex systems comprised of interacting autonomous agents. Open questions in agent-based simulation focus on scale-up issues encountered in simulating large numbers of agents. Specifically, how many agents can be included in a workable agent-based simulation? One of the basic tenets of agent-based modeling and simulation is that agents only interact and exchange locally available information with other agents located in their immediate proximity or neighborhood of the space in which the agents are situated. Generally, an agent's set of neighbors changes rapidly as a simulation proceeds through time and as the agents move through space. Depending on the topology defined for agent interactions, proximity may be defined by spatial distance for continuous space, adjacency for grid cells (as in cellular automata), or by connectivity in social networks. Identifying an agent's neighbors is a particularly time-consuming computational task and can dominate the computational effort in a simulation. Two challenges in agent simulation are (1) efficiently representing an agent's neighborhood and the neighbors in it and (2) efficiently identifying an agent's neighbors at any time in the simulation. These problems are addressed differently for different agent interaction topologies. While efficient approaches have been identified for agent neighborhood representation and neighbor identification for agents on a lattice with general neighborhood configurations, other techniques must be used when agents are able to move freely in space. Techniques for the analysis and representation of spatial data are applicable to the agent neighbor identification problem. This paper extends agent neighborhood simulation techniques from the lattice topology to continuous space, specifically R2. Algorithms based on hierarchical (quad trees) or non-hierarchical data structures (grid cells) are

  2. An Active Learning Exercise for Introducing Agent-Based Modeling

    ERIC Educational Resources Information Center

    Pinder, Jonathan P.

    2013-01-01

    Recent developments in agent-based modeling as a method of systems analysis and optimization indicate that students in business analytics need an introduction to the terminology, concepts, and framework of agent-based modeling. This article presents an active learning exercise for MBA students in business analytics that demonstrates agent-based…

  3. An Active Learning Exercise for Introducing Agent-Based Modeling

    ERIC Educational Resources Information Center

    Pinder, Jonathan P.

    2013-01-01

    Recent developments in agent-based modeling as a method of systems analysis and optimization indicate that students in business analytics need an introduction to the terminology, concepts, and framework of agent-based modeling. This article presents an active learning exercise for MBA students in business analytics that demonstrates agent-based…

  4. Agent-based model to rural urban migration analysis

    NASA Astrophysics Data System (ADS)

    Silveira, Jaylson J.; Espíndola, Aquino L.; Penna, T. J. P.

    2006-05-01

    In this paper, we analyze the rural-urban migration phenomenon as it is usually observed in economies which are in the early stages of industrialization. The analysis is conducted by means of a statistical mechanics approach which builds a computational agent-based model. Agents are placed on a lattice and the connections among them are described via an Ising-like model. Simulations on this computational model show some emergent properties that are common in developing economies, such as a transitional dynamics characterized by continuous growth of urban population, followed by the equalization of expected wages between rural and urban sectors (Harris-Todaro equilibrium condition), urban concentration and increasing of per capita income.

  5. Brief introductory guide to agent-based modeling and an illustration from urban health research.

    PubMed

    Auchincloss, Amy H; Garcia, Leandro Martin Totaro

    2015-11-01

    There is growing interest among urban health researchers in addressing complex problems using conceptual and computation models from the field of complex systems. Agent-based modeling (ABM) is one computational modeling tool that has received a lot of interest. However, many researchers remain unfamiliar with developing and carrying out an ABM, hindering the understanding and application of it. This paper first presents a brief introductory guide to carrying out a simple agent-based model. Then, the method is illustrated by discussing a previously developed agent-based model, which explored inequalities in diet in the context of urban residential segregation.

  6. Agent-Based Modeling of Growth Processes

    ERIC Educational Resources Information Center

    Abraham, Ralph

    2014-01-01

    Growth processes abound in nature, and are frequently the target of modeling exercises in the sciences. In this article we illustrate an agent-based approach to modeling, in the case of a single example from the social sciences: bullying.

  7. Agent-Based Modeling of Growth Processes

    ERIC Educational Resources Information Center

    Abraham, Ralph

    2014-01-01

    Growth processes abound in nature, and are frequently the target of modeling exercises in the sciences. In this article we illustrate an agent-based approach to modeling, in the case of a single example from the social sciences: bullying.

  8. Strengthening Theoretical Testing in Criminology Using Agent-based Modeling.

    PubMed

    Johnson, Shane D; Groff, Elizabeth R

    2014-07-01

    The Journal of Research in Crime and Delinquency (JRCD) has published important contributions to both criminological theory and associated empirical tests. In this article, we consider some of the challenges associated with traditional approaches to social science research, and discuss a complementary approach that is gaining popularity-agent-based computational modeling-that may offer new opportunities to strengthen theories of crime and develop insights into phenomena of interest. Two literature reviews are completed. The aim of the first is to identify those articles published in JRCD that have been the most influential and to classify the theoretical perspectives taken. The second is intended to identify those studies that have used an agent-based model (ABM) to examine criminological theories and to identify which theories have been explored. Ecological theories of crime pattern formation have received the most attention from researchers using ABMs, but many other criminological theories are amenable to testing using such methods. Traditional methods of theory development and testing suffer from a number of potential issues that a more systematic use of ABMs-not without its own issues-may help to overcome. ABMs should become another method in the criminologists toolbox to aid theory testing and falsification.

  9. Hypercompetitive Environments: An Agent-based model approach

    NASA Astrophysics Data System (ADS)

    Dias, Manuel; Araújo, Tanya

    Information technology (IT) environments are characterized by complex changes and rapid evolution. Globalization and the spread of technological innovation have increased the need for new strategic information resources, both from individual firms and management environments. Improvements in multidisciplinary methods and, particularly, the availability of powerful computational tools, are giving researchers an increasing opportunity to investigate management environments in their true complex nature. The adoption of a complex systems approach allows for modeling business strategies from a bottom-up perspective — understood as resulting from repeated and local interaction of economic agents — without disregarding the consequences of the business strategies themselves to individual behavior of enterprises, emergence of interaction patterns between firms and management environments. Agent-based models are at the leading approach of this attempt.

  10. Strengthening Theoretical Testing in Criminology Using Agent-based Modeling

    PubMed Central

    Groff, Elizabeth R.

    2014-01-01

    Objectives: The Journal of Research in Crime and Delinquency (JRCD) has published important contributions to both criminological theory and associated empirical tests. In this article, we consider some of the challenges associated with traditional approaches to social science research, and discuss a complementary approach that is gaining popularity—agent-based computational modeling—that may offer new opportunities to strengthen theories of crime and develop insights into phenomena of interest. Method: Two literature reviews are completed. The aim of the first is to identify those articles published in JRCD that have been the most influential and to classify the theoretical perspectives taken. The second is intended to identify those studies that have used an agent-based model (ABM) to examine criminological theories and to identify which theories have been explored. Results: Ecological theories of crime pattern formation have received the most attention from researchers using ABMs, but many other criminological theories are amenable to testing using such methods. Conclusion: Traditional methods of theory development and testing suffer from a number of potential issues that a more systematic use of ABMs—not without its own issues—may help to overcome. ABMs should become another method in the criminologists toolbox to aid theory testing and falsification. PMID:25419001

  11. Agent-based model of soil water dynamics

    NASA Astrophysics Data System (ADS)

    Mewes, Benjamin; Schumann, Andreas

    2017-04-01

    In the last decade, agent based modelling became more and more popular in social science, biology and environmental modelling. The concept is designed to simulate systems that are highly dynamic and sensitive to small variations in their composition and their state. As hydrological systems often show dynamic and nonlinear behaviour, agent based modelling can be an adequate way to model aquatic systems. Nevertheless, up to now only a few results on agent based modelling are known in hydrology. Processes like the percolation of water through the soil are highly responsive to the state of the pedological system. To simulate these water fluxes correctly by known approaches like the Green-Ampt model or approximations to the Richards equation, small time steps and a high spatial discretisation are needed. In this study a new approach for modelling water fluxes in a soil column is presented: autonomous water agents that transport water through the soil while interacting with their environment as well as with other agents under physical laws. Setting up an agent-based model requires a predefined rule set for the behaviour of the autonomous agents. Moreover, we present some principle assumptions of the interaction not only between agents, but as well between agents and their environment. Our study shows that agent-based modelling in hydrology leads to very promising results but we also have to face new challenges.

  12. Agent-based modeling of complex infrastructures

    SciTech Connect

    North, M. J.

    2001-06-01

    Complex Adaptive Systems (CAS) can be applied to investigate complex infrastructures and infrastructure interdependencies. The CAS model agents within the Spot Market Agent Research Tool (SMART) and Flexible Agent Simulation Toolkit (FAST) allow investigation of the electric power infrastructure, the natural gas infrastructure and their interdependencies.

  13. Agent-based computational model of the prevalence of gonococcal infections after the implementation of HIV pre-exposure prophylaxis guidelines

    PubMed Central

    Escobar, Erik; Durgham, Ryan; Dammann, Olaf; Stopka, Thomas J.

    2015-01-01

    Recently, the first comprehensive guidelines were published for pre-exposure prophylaxis (PrEP) for the prevention of HIV infection in populations with substantial risk of infection. Guidelines include a daily regimen of emtricitabine/tenofovir disoproxil fumarate (TDF/FTC) as well as condom usage during sexual activity. The relationship between the TDF/FTC intake regimen and condom usage is not yet fully understood. If men who have sex with men (MSM,) engage in high-risk sexual activities without using condoms when prescribed TDF/FTC they might be at an increased risk for other sexually transmitted diseases (STD). Our study focuses on the possible occurrence of behavioral changes among MSM in the United States over time with regard to condom usage. In particular, we were interested in creating a model of how increased uptake of TDF/FTC might cause a decline in condom usage, causing significant increases in non-HIV STD incidence, using gonococcal infection incidence as a biological endpoint. We used the agent-based modeling software NetLogo, building upon an existing model of HIV infection. We found no significant evidence for increased gonorrhea prevalence due to increased PrEP usage at any level of sample-wide usage, with a range of 0-90% PrEP usage. However, we did find significant evidence for decreased prevalence of HIV, with a maximal effect being reached when 5% to 10% of the MSM population used PrEP. Our findings appear to indicate that attitudes of aversion, within the medical community, toward the promotion of PrEP due to the potential risk of increased STD transmission are unfounded. PMID:26834937

  14. Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

    NASA Technical Reports Server (NTRS)

    Shameldin, Ramez Ahmed; Bowling, Shannon R.

    2010-01-01

    The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

  15. Mobile agent based online integration modeling for traffic information services

    NASA Astrophysics Data System (ADS)

    Li, Qingquan; Gao, Dequan; Fang, Zhixiang; Li, Lianying

    2007-06-01

    With the rapid development of urban economy and urbanization construction in China, traffic load rises sharply because of the larger vehicle occupancy within many urban areas, which has already led to serious traffic congestion problem. GIS-T is an efficient technological solution and core information infrastructure for solving modern urban transportation problems. High-level traffic systems must integrate real-time traffic information and spatial data of road to supply timely and efficient public services and guarantee a better orderly transportation. However, for traffic information is multisource, complex and massive, traffic information service must have fast, powerful capabilities for online integration processing. Online integration of traffic information emphasizes the traffic resources share and services optimization, and solve assignment, scheduling, monitoring and feedback of integration computing tasks in dynamic and distributed network. This paper firstly analyzes traffic data and existing problems of online integration, and then discusses mobile agent technology, and finally proposes a mobile agent based unified online integration model of traffic information. This model will achieve cooperative computing and more accessible, flexible and reliable traffic information services.

  16. Diversity and Community: The Role of Agent-Based Modeling.

    PubMed

    Stivala, Alex

    2017-03-13

    Community psychology involves several dialectics between potentially opposing ideals, such as theory and practice, rights and needs, and respect for human diversity and sense of community. Some recent papers in the American Journal of Community Psychology have examined the diversity-community dialectic, some with the aid of agent-based modeling and concepts from network science. This paper further elucidates these concepts and suggests that research in community psychology can benefit from a useful dialectic between agent-based modeling and the real-world concerns of community psychology.

  17. A Large Scale, High Resolution Agent-Based Insurgency Model

    DTIC Science & Technology

    2013-09-30

    2007). HSCB Models can be employed for simulating mission scenarios, determining optimal strategies for disrupting terrorist networks, or training and...High Resolution Agent-Based Insurgency Model ∑ = ⎜ ⎜ ⎝ ⎛ − −− = desired 1 move,desired, desired,,desired, desired,, N j ij jmoveij moveiD rp prp

  18. A Coupled Simulation Architecture for Agent-Based/Geohydrological Modelling

    NASA Astrophysics Data System (ADS)

    Jaxa-Rozen, M.

    2016-12-01

    The quantitative modelling of social-ecological systems can provide useful insights into the interplay between social and environmental processes, and their impact on emergent system dynamics. However, such models should acknowledge the complexity and uncertainty of both of the underlying subsystems. For instance, the agent-based models which are increasingly popular for groundwater management studies can be made more useful by directly accounting for the hydrological processes which drive environmental outcomes. Conversely, conventional environmental models can benefit from an agent-based depiction of the feedbacks and heuristics which influence the decisions of groundwater users. From this perspective, this work describes a Python-based software architecture which couples the popular NetLogo agent-based platform with the MODFLOW/SEAWAT geohydrological modelling environment. This approach enables users to implement agent-based models in NetLogo's user-friendly platform, while benefiting from the full capabilities of MODFLOW/SEAWAT packages or reusing existing geohydrological models. The software architecture is based on the pyNetLogo connector, which provides an interface between the NetLogo agent-based modelling software and the Python programming language. This functionality is then extended and combined with Python's object-oriented features, to design a simulation architecture which couples NetLogo with MODFLOW/SEAWAT through the FloPy library (Bakker et al., 2016). The Python programming language also provides access to a range of external packages which can be used for testing and analysing the coupled models, which is illustrated for an application of Aquifer Thermal Energy Storage (ATES).

  19. Cognitive Modeling for Agent-Based Simulation of Child Maltreatment

    NASA Astrophysics Data System (ADS)

    Hu, Xiaolin; Puddy, Richard

    This paper extends previous work to develop cognitive modeling for agent-based simulation of child maltreatment (CM). The developed model is inspired from parental efficacy, parenting stress, and the theory of planned behavior. It provides an explanatory, process-oriented model of CM and incorporates causality relationship and feedback loops from different factors in the social ecology in order for simulating the dynamics of CM. We describe the model and present simulation results to demonstrate the features of this model.

  20. Endogenizing geopolitical boundaries with agent-based modeling

    PubMed Central

    Cederman, Lars-Erik

    2002-01-01

    Agent-based modeling promises to overcome the reification of actors. Whereas this common, but limiting, assumption makes a lot of sense during periods characterized by stable actor boundaries, other historical junctures, such as the end of the Cold War, exhibit far-reaching and swift transformations of actors' spatial and organizational existence. Moreover, because actors cannot be assumed to remain constant in the long run, analysis of macrohistorical processes virtually always requires “sociational” endogenization. This paper presents a series of computational models, implemented with the software package REPAST, which trace complex macrohistorical transformations of actors be they hierarchically organized as relational networks or as collections of symbolic categories. With respect to the former, dynamic networks featuring emergent compound actors with agent compartments represented in a spatial grid capture organizational domination of the territorial state. In addition, models of “tagged” social processes allows the analyst to show how democratic states predicate their behavior on categorical traits. Finally, categorical schemata that select out politically relevant cultural traits in ethnic landscapes formalize a constructivist notion of national identity in conformance with the qualitative literature on nationalism. This “finite-agent method”, representing both states and nations as higher-level structures superimposed on a lower-level grid of primitive agents or cultural traits, avoids reification of agency. Furthermore, it opens the door to explicit analysis of entity processes, such as the integration and disintegration of actors as well as boundary transformations. PMID:12011409

  1. Adding ecosystem function to agent-based land use models

    USDA-ARS?s Scientific Manuscript database

    The objective of this paper is to examine issues in the inclusion of simulations of ecosystem functions in agent-based models of land use decision-making. The reasons for incorporating these simulations include local interests in land fertility and global interests in carbon sequestration. Biogeoche...

  2. The fractional volatility model: An agent-based interpretation

    NASA Astrophysics Data System (ADS)

    Vilela Mendes, R.

    2008-06-01

    Based on the criteria of mathematical simplicity and consistency with empirical market data, a model with volatility driven by fractional noise has been constructed which provides a fairly accurate mathematical parametrization of the data. Here, some features of the model are reviewed and extended to account for leverage effects. Using agent-based models, one tries to find which agent strategies and (or) properties of the financial institutions might be responsible for the features of the fractional volatility model.

  3. Using Model Replication to Improve the Reliability of Agent-Based Models

    NASA Astrophysics Data System (ADS)

    Zhong, Wei; Kim, Yushim

    The basic presupposition of model replication activities for a computational model such as an agent-based model (ABM) is that, as a robust and reliable tool, it must be replicable in other computing settings. This assumption has recently gained attention in the community of artificial society and simulation due to the challenges of model verification and validation. Illustrating the replication of an ABM representing fraudulent behavior in a public service delivery system originally developed in the Java-based MASON toolkit for NetLogo by a different author, this paper exemplifies how model replication exercises provide unique opportunities for model verification and validation process. At the same time, it helps accumulate best practices and patterns of model replication and contributes to the agenda of developing a standard methodological protocol for agent-based social simulation.

  4. Tutorial on agent-based modeling and simulation. Part 2 : how to model with agents.

    SciTech Connect

    Macal, C. M.; North, M. J.; Decision and Information Sciences

    2006-01-01

    Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of interacting autonomous agents. ABMS promises to have far-reaching effects on the way that businesses use computers to support decision-making and researchers use electronic laboratories to do research. Some have gone so far as to contend that ABMS is a new way of doing science. Computational advances make possible a growing number of agent-based applications across many fields. Applications range from modeling agent behavior in the stock market and supply chains, to predicting the spread of epidemics and the threat of bio-warfare, from modeling the growth and decline of ancient civilizations to modeling the complexities of the human immune system, and many more. This tutorial describes the foundations of ABMS, identifies ABMS toolkits and development methods illustrated through a supply chain example, and provides thoughts on the appropriate contexts for ABMS versus conventional modeling techniques.

  5. Agent-based Modeling with MATSim for Hazards Evacuation Planning

    NASA Astrophysics Data System (ADS)

    Jones, J. M.; Ng, P.; Henry, K.; Peters, J.; Wood, N. J.

    2015-12-01

    Hazard evacuation planning requires robust modeling tools and techniques, such as least cost distance or agent-based modeling, to gain an understanding of a community's potential to reach safety before event (e.g. tsunami) arrival. Least cost distance modeling provides a static view of the evacuation landscape with an estimate of travel times to safety from each location in the hazard space. With this information, practitioners can assess a community's overall ability for timely evacuation. More information may be needed if evacuee congestion creates bottlenecks in the flow patterns. Dynamic movement patterns are best explored with agent-based models that simulate movement of and interaction between individual agents as evacuees through the hazard space, reacting to potential congestion areas along the evacuation route. The multi-agent transport simulation model MATSim is an agent-based modeling framework that can be applied to hazard evacuation planning. Developed jointly by universities in Switzerland and Germany, MATSim is open-source software written in Java and freely available for modification or enhancement. We successfully used MATSim to illustrate tsunami evacuation challenges in two island communities in California, USA, that are impacted by limited escape routes. However, working with MATSim's data preparation, simulation, and visualization modules in an integrated development environment requires a significant investment of time to develop the software expertise to link the modules and run a simulation. To facilitate our evacuation research, we packaged the MATSim modules into a single application tailored to the needs of the hazards community. By exposing the modeling parameters of interest to researchers in an intuitive user interface and hiding the software complexities, we bring agent-based modeling closer to practitioners and provide access to the powerful visual and analytic information that this modeling can provide.

  6. Validation techniques of agent based modelling for geospatial simulations

    NASA Astrophysics Data System (ADS)

    Darvishi, M.; Ahmadi, G.

    2014-10-01

    One of the most interesting aspects of modelling and simulation study is to describe the real world phenomena that have specific properties; especially those that are in large scales and have dynamic and complex behaviours. Studying these phenomena in the laboratory is costly and in most cases it is impossible. Therefore, Miniaturization of world phenomena in the framework of a model in order to simulate the real phenomena is a reasonable and scientific approach to understand the world. Agent-based modelling and simulation (ABMS) is a new modelling method comprising of multiple interacting agent. They have been used in the different areas; for instance, geographic information system (GIS), biology, economics, social science and computer science. The emergence of ABM toolkits in GIS software libraries (e.g. ESRI's ArcGIS, OpenMap, GeoTools, etc) for geospatial modelling is an indication of the growing interest of users to use of special capabilities of ABMS. Since ABMS is inherently similar to human cognition, therefore it could be built easily and applicable to wide range applications than a traditional simulation. But a key challenge about ABMS is difficulty in their validation and verification. Because of frequent emergence patterns, strong dynamics in the system and the complex nature of ABMS, it is hard to validate and verify ABMS by conventional validation methods. Therefore, attempt to find appropriate validation techniques for ABM seems to be necessary. In this paper, after reviewing on Principles and Concepts of ABM for and its applications, the validation techniques and challenges of ABM validation are discussed.

  7. SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

    PubMed

    Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

    2010-01-01

    Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

  8. Tutorial on Agent-based Modeling and Simulation

    DTIC Science & Technology

    2007-06-01

    World of Science. New York: Wiley Crichton , Michael , 2002, Prey, HarperCollins. Epstein JM, Axtell R. 1996. Growing Artificial Societies...other author(s): Michael J. North and Charles M. Macal Principal Author’s Organization and address: Argonne National Laboratory 9700 S. Cass Avenue...on Agent-based Modeling and Simulation Michael J. North and Charles M. Macal Center for Complex Adaptive Agent Systems Simulation (CAS2) Decision

  9. Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth.

    PubMed

    Poleszczuk, Jan; Macklin, Paul; Enderling, Heiko

    2016-01-01

    Computational modeling of tumor growth has become an invaluable tool to simulate complex cell-cell interactions and emerging population-level dynamics. Agent-based models are commonly used to describe the behavior and interaction of individual cells in different environments. Behavioral rules can be informed and calibrated by in vitro assays, and emerging population-level dynamics may be validated with both in vitro and in vivo experiments. Here, we describe the design and implementation of a lattice-based agent-based model of cancer stem cell driven tumor growth.

  10. Agent-based model of macrophage action on endocrine pancreas.

    PubMed

    Martínez, Ignacio V; Gómez, Enrique J; Hernando, M Elena; Villares, Ricardo; Mellado, Mario

    2012-01-01

    This paper proposes an agent-based model of the action of macrophages on the beta cells of the endocrine pancreas. The aim of this model is to simulate the processes of beta cell proliferation and apoptosis and also the process of phagocytosis of cell debris by macrophages, all of which are related to the onset of the autoimmune response in type 1 diabetes. We have used data from the scientific literature to design the model. The results show that the model obtains good approximations to real processes and could be used to shed light on some open questions concerning such processes.

  11. From Compartmentalized to Agent-based Models of Epidemics

    NASA Astrophysics Data System (ADS)

    Macal, Charles

    Supporting decisions in the throes of an impending epidemic poses distinct technical challenges arising from the uncertainties in modeling disease propagation processes and the need for producing timely answers to policy questions. Compartmental models, because of their relative simplicity, produce timely information, but often do not include the level of fidelity of the information needed to answer specific policy questions. Highly granular agent-based simulations produce an extensive amount of information on all aspects of a simulated epidemic, yet complex models often cannot produce this information in a timely manner. We propose a two-phased approach to addressing the tradeoff between model complexity and the speed at which models can be used to answer to questions about an impending outbreak. In the first phase, in advance of an epidemic, ensembles of highly granular agent-based simulations are run over the entire parameter space, characterizing the space of possible model outcomes and uncertainties. Meta-models are derived that characterize model outcomes as dependent on uncertainties in disease parameters, data, and structural relationships. In the second phase, envisioned as during an epidemic, the meta-model is run in combination with compartmental models, which can be run very quickly. Model outcomes are compared as a basis for establishing uncertainties in model forecasts. This work is supported by the U.S. Department of Energy under Contract number DE-AC02-06CH11357 and National Science Foundation (NSF) RAPID Award DEB-1516428.

  12. Agent-Based Deterministic Modeling of the Bone Marrow Homeostasis

    PubMed Central

    2016-01-01

    Modeling of stem cells not only describes but also predicts how a stem cell's environment can control its fate. The first stem cell populations discovered were hematopoietic stem cells (HSCs). In this paper, we present a deterministic model of bone marrow (that hosts HSCs) that is consistent with several of the qualitative biological observations. This model incorporates stem cell death (apoptosis) after a certain number of cell divisions and also demonstrates that a single HSC can potentially populate the entire bone marrow. It also demonstrates that there is a production of sufficient number of differentiated cells (RBCs, WBCs, etc.). We prove that our model of bone marrow is biologically consistent and it overcomes the biological feasibility limitations of previously reported models. The major contribution of our model is the flexibility it allows in choosing model parameters which permits several different simulations to be carried out in silico without affecting the homeostatic properties of the model. We have also performed agent-based simulation of the model of bone marrow system proposed in this paper. We have also included parameter details and the results obtained from the simulation. The program of the agent-based simulation of the proposed model is made available on a publicly accessible website. PMID:27340402

  13. Agent-Based Deterministic Modeling of the Bone Marrow Homeostasis.

    PubMed

    Kurhekar, Manish; Deshpande, Umesh

    2016-01-01

    Modeling of stem cells not only describes but also predicts how a stem cell's environment can control its fate. The first stem cell populations discovered were hematopoietic stem cells (HSCs). In this paper, we present a deterministic model of bone marrow (that hosts HSCs) that is consistent with several of the qualitative biological observations. This model incorporates stem cell death (apoptosis) after a certain number of cell divisions and also demonstrates that a single HSC can potentially populate the entire bone marrow. It also demonstrates that there is a production of sufficient number of differentiated cells (RBCs, WBCs, etc.). We prove that our model of bone marrow is biologically consistent and it overcomes the biological feasibility limitations of previously reported models. The major contribution of our model is the flexibility it allows in choosing model parameters which permits several different simulations to be carried out in silico without affecting the homeostatic properties of the model. We have also performed agent-based simulation of the model of bone marrow system proposed in this paper. We have also included parameter details and the results obtained from the simulation. The program of the agent-based simulation of the proposed model is made available on a publicly accessible website.

  14. Model reduction for agent-based social simulation: Coarse-graining a civil violence model

    NASA Astrophysics Data System (ADS)

    Zou, Yu; Fonoberov, Vladimir A.; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G.

    2012-06-01

    Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

  15. Model reduction for agent-based social simulation: coarse-graining a civil violence model.

    PubMed

    Zou, Yu; Fonoberov, Vladimir A; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G

    2012-06-01

    Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

  16. Numerical Problems and Agent-Based Models for a Mass Transfer Course

    ERIC Educational Resources Information Center

    Murthi, Manohar; Shea, Lonnie D.; Snurr, Randall Q.

    2009-01-01

    Problems requiring numerical solutions of differential equations or the use of agent-based modeling are presented for use in a course on mass transfer. These problems were solved using the popular technical computing language MATLABTM. Students were introduced to MATLAB via a problem with an analytical solution. A more complex problem to which no…

  17. Numerical Problems and Agent-Based Models for a Mass Transfer Course

    ERIC Educational Resources Information Center

    Murthi, Manohar; Shea, Lonnie D.; Snurr, Randall Q.

    2009-01-01

    Problems requiring numerical solutions of differential equations or the use of agent-based modeling are presented for use in a course on mass transfer. These problems were solved using the popular technical computing language MATLABTM. Students were introduced to MATLAB via a problem with an analytical solution. A more complex problem to which no…

  18. Evaluation of development prospects of renewable energy: agent based modelling

    NASA Astrophysics Data System (ADS)

    Klevakina, E. A.; Zabelina, I. A.; Murtazina, M. Sh

    2017-01-01

    The paper describes the agent-based model usage to evaluate the dynamics and the perspectives of alternative energy adopting in the Eastern regions of Russia. It includes a brief review of the agent-based models that can be used for estimation of alternatives in the process of transition to “green” economics. The authors show that active usage of solar energy in Russia is possible at the rural household level, when the climate conditions are appropriate. Adoption of solar energy sources decreases the energy production based on the conventional sources and improves the quality of environment in the regions. A complex regional multi-agent model is considered in this paper. The model consists of several private models and uses GIS technologies. These private models are a demographic and migration model of the region and a diffusion of the innovations model. In these models, agents are humans who live within the boundaries of the agents-municipalities, and agents as well are large-scale producers of electricity that pollutes the environment. Such a structure allows us to determine the changes in the demand for electricity generated by traditional sources. A simulation software will assist to identify the opportunities for implementation of alternative energy sources in the Eastern regions of Russia.

  19. Can agent based models effectively reduce fisheries management implementation uncertainty?

    NASA Astrophysics Data System (ADS)

    Drexler, M.

    2016-02-01

    Uncertainty is an inherent feature of fisheries management. Implementation uncertainty remains a challenge to quantify often due to unintended responses of users to management interventions. This problem will continue to plague both single species and ecosystem based fisheries management advice unless the mechanisms driving these behaviors are properly understood. Equilibrium models, where each actor in the system is treated as uniform and predictable, are not well suited to forecast the unintended behaviors of individual fishers. Alternatively, agent based models (AMBs) can simulate the behaviors of each individual actor driven by differing incentives and constraints. This study evaluated the feasibility of using AMBs to capture macro scale behaviors of the US West Coast Groundfish fleet. Agent behavior was specified at the vessel level. Agents made daily fishing decisions using knowledge of their own cost structure, catch history, and the histories of catch and quota markets. By adding only a relatively small number of incentives, the model was able to reproduce highly realistic macro patterns of expected outcomes in response to management policies (catch restrictions, MPAs, ITQs) while preserving vessel heterogeneity. These simulations indicate that agent based modeling approaches hold much promise for simulating fisher behaviors and reducing implementation uncertainty. Additional processes affecting behavior, informed by surveys, are continually being added to the fisher behavior model. Further coupling of the fisher behavior model to a spatial ecosystem model will provide a fully integrated social, ecological, and economic model capable of performing management strategy evaluations to properly consider implementation uncertainty in fisheries management.

  20. An Agent Based Model for Social Class Emergence

    NASA Astrophysics Data System (ADS)

    Yang, Xiaoxiang; Rodriguez Segura, Daniel; Lin, Fei; Mazilu, Irina

    We present an open system agent-based model to analyze the effects of education and the society-specific wealth transactions on the emergence of social classes. Building on previous studies, we use realistic functions to model how years of education affect the income level. Numerical simulations show that the fraction of an individual's total transactions that is invested rather than consumed can cause wealth gaps between different income brackets in the long run. In an attempt to incorporate the network effects, we also explore how the probability of interactions among agents depending on the spread of their income brackets affects wealth distribution.

  1. Techniques and Issues in Agent-Based Modeling Validation

    SciTech Connect

    Pullum, Laura L; Cui, Xiaohui

    2012-01-01

    Validation of simulation models is extremely important. It ensures that the right model has been built and lends confidence to the use of that model to inform critical decisions. Agent-based models (ABM) have been widely deployed in different fields for studying the collective behavior of large numbers of interacting agents. However, researchers have only recently started to consider the issues of validation. Compared to other simulation models, ABM has many differences in model development, usage and validation. An ABM is inherently easier to build than a classical simulation, but more difficult to describe formally since they are closer to human cognition. Using multi-agent models to study complex systems has attracted criticisms because of the challenges involved in their validation [1]. In this report, we describe the challenge of ABM validation and present a novel approach we recently developed for an ABM system.

  2. Agent-based modeling and systems dynamics model reproduction.

    SciTech Connect

    North, M. J.; Macal, C. M.

    2009-01-01

    Reproducibility is a pillar of the scientific endeavour. We view computer simulations as laboratories for electronic experimentation and therefore as tools for science. Recent studies have addressed model reproduction and found it to be surprisingly difficult to replicate published findings. There have been enough failed simulation replications to raise the question, 'can computer models be fully replicated?' This paper answers in the affirmative by reporting on a successful reproduction study using Mathematica, Repast and Swarm for the Beer Game supply chain model. The reproduction process was valuable because it demonstrated the original result's robustness across modelling methodologies and implementation environments.

  3. Agent-based modeling: case study in cleavage furrow models

    PubMed Central

    Mogilner, Alex; Manhart, Angelika

    2016-01-01

    The number of studies in cell biology in which quantitative models accompany experiments has been growing steadily. Roughly, mathematical and computational techniques of these models can be classified as “differential equation based” (DE) or “agent based” (AB). Recently AB models have started to outnumber DE models, but understanding of AB philosophy and methodology is much less widespread than familiarity with DE techniques. Here we use the history of modeling a fundamental biological problem—positioning of the cleavage furrow in dividing cells—to explain how and why DE and AB models are used. We discuss differences, advantages, and shortcomings of these two approaches. PMID:27811328

  4. Modelling of robotic work cells using agent based-approach

    NASA Astrophysics Data System (ADS)

    Sękala, A.; Banaś, W.; Gwiazda, A.; Monica, Z.; Kost, G.; Hryniewicz, P.

    2016-08-01

    In the case of modern manufacturing systems the requirements, both according the scope and according characteristics of technical procedures are dynamically changing. This results in production system organization inability to keep up with changes in a market demand. Accordingly, there is a need for new design methods, characterized, on the one hand with a high efficiency and on the other with the adequate level of the generated organizational solutions. One of the tools that could be used for this purpose is the concept of agent systems. These systems are the tools of artificial intelligence. They allow assigning to agents the proper domains of procedures and knowledge so that they represent in a self-organizing system of an agent environment, components of a real system. The agent-based system for modelling robotic work cell should be designed taking into consideration many limitations considered with the characteristic of this production unit. It is possible to distinguish some grouped of structural components that constitute such a system. This confirms the structural complexity of a work cell as a specific production system. So it is necessary to develop agents depicting various aspects of the work cell structure. The main groups of agents that are used to model a robotic work cell should at least include next pattern representatives: machine tool agents, auxiliary equipment agents, robots agents, transport equipment agents, organizational agents as well as data and knowledge bases agents. In this way it is possible to create the holarchy of the agent-based system.

  5. Climate Shocks and Migration: An Agent-Based Modeling Approach

    PubMed Central

    Entwisle, Barbara; Williams, Nathalie E.; Verdery, Ashton M.; Rindfuss, Ronald R.; Walsh, Stephen J.; Malanson, George P.; Mucha, Peter J.; Frizzelle, Brian G.; McDaniel, Philip M.; Yao, Xiaozheng; Heumann, Benjamin W.; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree

    2016-01-01

    This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, ‘normal’ scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response. PMID:27594725

  6. Climate Shocks and Migration: An Agent-Based Modeling Approach.

    PubMed

    Entwisle, Barbara; Williams, Nathalie E; Verdery, Ashton M; Rindfuss, Ronald R; Walsh, Stephen J; Malanson, George P; Mucha, Peter J; Frizzelle, Brian G; McDaniel, Philip M; Yao, Xiaozheng; Heumann, Benjamin W; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree

    2016-09-01

    This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, 'normal' scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response.

  7. Using Agent Based Modeling (ABM) to Develop Cultural Interaction Simulations

    NASA Technical Reports Server (NTRS)

    Drucker, Nick; Jones, Phillip N.

    2012-01-01

    Today, most cultural training is based on or built around "cultural engagements" or discrete interactions between the individual learner and one or more cultural "others". Often, success in the engagement is the end or the objective. In reality, these interactions usually involve secondary and tertiary effects with potentially wide ranging consequences. The concern is that learning culture within a strict engagement context might lead to "checklist" cultural thinking that will not empower learners to understand the full consequence of their actions. We propose the use of agent based modeling (ABM) to collect, store, and, simulating the effects of social networks, promulgate engagement effects over time, distance, and consequence. The ABM development allows for rapid modification to re-create any number of population types, extending the applicability of the model to any requirement for social modeling.

  8. Agent-Based Modeling of Noncommunicable Diseases: A Systematic Review

    PubMed Central

    Arah, Onyebuchi A.

    2015-01-01

    We reviewed the use of agent-based modeling (ABM), a systems science method, in understanding noncommunicable diseases (NCDs) and their public health risk factors. We systematically reviewed studies in PubMed, ScienceDirect, and Web of Sciences published from January 2003 to July 2014. We retrieved 22 relevant articles; each had an observational or interventional design. Physical activity and diet were the most-studied outcomes. Often, single agent types were modeled, and the environment was usually irrelevant to the studied outcome. Predictive validation and sensitivity analyses were most used to validate models. Although increasingly used to study NCDs, ABM remains underutilized and, where used, is suboptimally reported in public health studies. Its use in studying NCDs will benefit from clarified best practices and improved rigor to establish its usefulness and facilitate replication, interpretation, and application. PMID:25602871

  9. Agent-based cognitive model for human resources competence management.

    PubMed

    Oliveira, Stefan; Gluz, João Carlos

    2010-01-01

    This chapter presents an agent-based cognitive model aimed to represent human competency concepts and competence management processes of psychological nature. This model is implemented by a multiagent system application intended to help managers of software development projects to select, based on the competence management model, the right professionals to integrate a development team. There are several software engineering methodologies that can be used to design and develop multiagent systems. However, due to the necessity to handle human competency concepts of cognitive nature, like aptitudes, interests, abilities and knowledge, we were driven to choose methodologies that can handle these concepts since the inception of the system. To do so, we integrated the TROPOS methodology, and a set of software engineering methods derived from intelligent tutoring systems research to successfully analyze and design the proposed system. At the end of the paper we present a study case, showing how the proposed system should be applied to the domain of website development.

  10. Agent-based modeling of noncommunicable diseases: a systematic review.

    PubMed

    Nianogo, Roch A; Arah, Onyebuchi A

    2015-03-01

    We reviewed the use of agent-based modeling (ABM), a systems science method, in understanding noncommunicable diseases (NCDs) and their public health risk factors. We systematically reviewed studies in PubMed, ScienceDirect, and Web of Sciences published from January 2003 to July 2014. We retrieved 22 relevant articles; each had an observational or interventional design. Physical activity and diet were the most-studied outcomes. Often, single agent types were modeled, and the environment was usually irrelevant to the studied outcome. Predictive validation and sensitivity analyses were most used to validate models. Although increasingly used to study NCDs, ABM remains underutilized and, where used, is suboptimally reported in public health studies. Its use in studying NCDs will benefit from clarified best practices and improved rigor to establish its usefulness and facilitate replication, interpretation, and application.

  11. Agent-Based Multicellular Modeling for Predictive Toxicology

    EPA Science Inventory

    Biological modeling is a rapidly growing field that has benefited significantly from recent technological advances, expanding traditional methods with greater computing power, parameter-determination algorithms, and the development of novel computational approaches to modeling bi...

  12. Agent-Based Multicellular Modeling for Predictive Toxicology

    EPA Science Inventory

    Biological modeling is a rapidly growing field that has benefited significantly from recent technological advances, expanding traditional methods with greater computing power, parameter-determination algorithms, and the development of novel computational approaches to modeling bi...

  13. Statistical Agent Based Modelization of the Phenomenon of Drug Abuse

    NASA Astrophysics Data System (ADS)

    di Clemente, Riccardo; Pietronero, Luciano

    2012-07-01

    We introduce a statistical agent based model to describe the phenomenon of drug abuse and its dynamical evolution at the individual and global level. The agents are heterogeneous with respect to their intrinsic inclination to drugs, to their budget attitude and social environment. The various levels of drug use were inspired by the professional description of the phenomenon and this permits a direct comparison with all available data. We show that certain elements have a great importance to start the use of drugs, for example the rare events in the personal experiences which permit to overcame the barrier of drug use occasionally. The analysis of how the system reacts to perturbations is very important to understand its key elements and it provides strategies for effective policy making. The present model represents the first step of a realistic description of this phenomenon and can be easily generalized in various directions.

  14. Addressing the translational dilemma: dynamic knowledge representation of inflammation using agent-based modeling.

    PubMed

    An, Gary; Christley, Scott

    2012-01-01

    Given the panoply of system-level diseases that result from disordered inflammation, such as sepsis, atherosclerosis, cancer, and autoimmune disorders, understanding and characterizing the inflammatory response is a key target of biomedical research. Untangling the complex behavioral configurations associated with a process as ubiquitous as inflammation represents a prototype of the translational dilemma: the ability to translate mechanistic knowledge into effective therapeutics. A critical failure point in the current research environment is a throughput bottleneck at the level of evaluating hypotheses of mechanistic causality; these hypotheses represent the key step toward the application of knowledge for therapy development and design. Addressing the translational dilemma will require utilizing the ever-increasing power of computers and computational modeling to increase the efficiency of the scientific method in the identification and evaluation of hypotheses of mechanistic causality. More specifically, development needs to focus on facilitating the ability of non-computer trained biomedical researchers to utilize and instantiate their knowledge in dynamic computational models. This is termed "dynamic knowledge representation." Agent-based modeling is an object-oriented, discrete-event, rule-based simulation method that is well suited for biomedical dynamic knowledge representation. Agent-based modeling has been used in the study of inflammation at multiple scales. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggest that this modeling framework is well suited for addressing the translational dilemma. This review describes agent-based modeling, gives examples of its applications in the study of inflammation, and introduces a proposed general expansion of the use of modeling and simulation to augment the generation and evaluation of knowledge

  15. Research on monocentric model of urbanization by agent-based simulation

    NASA Astrophysics Data System (ADS)

    Xue, Ling; Yang, Kaizhong

    2008-10-01

    Over the past years, GIS have been widely used for modeling urbanization from a variety of perspectives such as digital terrain representation and overlay analysis using cell-based data platform. Similarly, simulation of urban dynamics has been achieved with the use of Cellular Automata. In contrast to these approaches, agent-based simulation provides a much more powerful set of tools. This allows researchers to set up a counterpart for real environmental and urban systems in computer for experimentation and scenario analysis. This Paper basically reviews the research on the economic mechanism of urbanization and an agent-based monocentric model is setup for further understanding the urbanization process and mechanism in China. We build an endogenous growth model with dynamic interactions between spatial agglomeration and urban development by using agent-based simulation. It simulates the migration decisions of two main types of agents, namely rural and urban households between rural and urban area. The model contains multiple economic interactions that are crucial in understanding urbanization and industrial process in China. These adaptive agents can adjust their supply and demand according to the market situation by a learning algorithm. The simulation result shows this agent-based urban model is able to perform the regeneration and to produce likely-to-occur projections of reality.

  16. An equation-free approach to agent-based computation: Bifurcation analysis and control of stationary states

    NASA Astrophysics Data System (ADS)

    Siettos, C. I.; Gear, C. W.; Kevrekidis, I. G.

    2012-08-01

    We show how the equation-free approach can be exploited to enable agent-based simulators to perform system-level computations such as bifurcation, stability analysis and controller design. We illustrate these tasks through an event-driven agent-based model describing the dynamic behaviour of many interacting investors in the presence of mimesis. Using short bursts of appropriately initialized runs of the detailed, agent-based simulator, we construct the coarse-grained bifurcation diagram of the (expected) density of agents and investigate the stability of its multiple solution branches. When the mimetic coupling between agents becomes strong enough, the stable stationary state loses its stability at a coarse turning point bifurcation. We also demonstrate how the framework can be used to design a wash-out dynamic controller that stabilizes open-loop unstable stationary states even under model uncertainty.

  17. Biotechnology on the Battlefield: An Application of Agent-based Modelling for Emerging Technology Assessment

    DTIC Science & Technology

    2015-03-01

    UNCLASSIFIED UNCLASSIFIED Biotechnology on the Battlefield: An Application of Agent- based Modelling for Emerging Technology Assessment...data from the Vietnam War and assessed through a process of simulation in an agent- based combat environment. Finally, we conclude that the drug...of Agent- based Modelling for Emerging Technology Assessment Executive Summary Biotechnologies have the capacity to enhance the performance of

  18. Evaluating Water Demand Using Agent-Based Modeling

    NASA Astrophysics Data System (ADS)

    Lowry, T. S.

    2004-12-01

    The supply and demand of water resources are functions of complex, inter-related systems including hydrology, climate, demographics, economics, and policy. To assess the safety and sustainability of water resources, planners often rely on complex numerical models that relate some or all of these systems using mathematical abstractions. The accuracy of these models relies on how well the abstractions capture the true nature of the systems interactions. Typically, these abstractions are based on analyses of observations and/or experiments that account only for the statistical mean behavior of each system. This limits the approach in two important ways: 1) It cannot capture cross-system disruptive events, such as major drought, significant policy change, or terrorist attack, and 2) it cannot resolve sub-system level responses. To overcome these limitations, we are developing an agent-based water resources model that includes the systems of hydrology, climate, demographics, economics, and policy, to examine water demand during normal and extraordinary conditions. Agent-based modeling (ABM) develops functional relationships between systems by modeling the interaction between individuals (agents), who behave according to a probabilistic set of rules. ABM is a "bottom-up" modeling approach in that it defines macro-system behavior by modeling the micro-behavior of individual agents. While each agent's behavior is often simple and predictable, the aggregate behavior of all agents in each system can be complex, unpredictable, and different than behaviors observed in mean-behavior models. Furthermore, the ABM approach creates a virtual laboratory where the effects of policy changes and/or extraordinary events can be simulated. Our model, which is based on the demographics and hydrology of the Middle Rio Grande Basin in the state of New Mexico, includes agent groups of residential, agricultural, and industrial users. Each agent within each group determines its water usage

  19. Improving Agent Based Models and Validation through Data Fusion

    PubMed Central

    Laskowski, Marek; Demianyk, Bryan C.P.; Friesen, Marcia R.; McLeod, Robert D.; Mukhi, Shamir N.

    2011-01-01

    This work is contextualized in research in modeling and simulation of infection spread within a community or population, with the objective to provide a public health and policy tool in assessing the dynamics of infection spread and the qualitative impacts of public health interventions. This work uses the integration of real data sources into an Agent Based Model (ABM) to simulate respiratory infection spread within a small municipality. Novelty is derived in that the data sources are not necessarily obvious within ABM infection spread models. The ABM is a spatial-temporal model inclusive of behavioral and interaction patterns between individual agents on a real topography. The agent behaviours (movements and interactions) are fed by census / demographic data, integrated with real data from a telecommunication service provider (cellular records) and person-person contact data obtained via a custom 3G Smartphone application that logs Bluetooth connectivity between devices. Each source provides data of varying type and granularity, thereby enhancing the robustness of the model. The work demonstrates opportunities in data mining and fusion that can be used by policy and decision makers. The data become real-world inputs into individual SIR disease spread models and variants, thereby building credible and non-intrusive models to qualitatively simulate and assess public health interventions at the population level. PMID:23569606

  20. Architectural considerations for agent-based national scale policy models : LDRD final report.

    SciTech Connect

    Backus, George A.; Strip, David R.

    2007-09-01

    The need to anticipate the consequences of policy decisions becomes ever more important as the magnitude of the potential consequences grows. The multiplicity of connections between the components of society and the economy makes intuitive assessments extremely unreliable. Agent-based modeling has the potential to be a powerful tool in modeling policy impacts. The direct mapping between agents and elements of society and the economy simplify the mapping of real world functions into the world of computation assessment. Our modeling initiative is motivated by the desire to facilitate informed public debate on alternative policies for how we, as a nation, provide healthcare to our population. We explore the implications of this motivation on the design and implementation of a model. We discuss the choice of an agent-based modeling approach and contrast it to micro-simulation and systems dynamics approaches.

  1. An agent-based mathematical model about carp aggregation

    NASA Astrophysics Data System (ADS)

    Liang, Yu; Wu, Chao

    2005-05-01

    This work presents an agent-based mathematical model to simulate the aggregation of carp, a harmful fish in North America. The referred mathematical model is derived from the following assumptions: (1) instead of the consensus among every carps involved in the aggregation, the aggregation of carp is completely a random and spontaneous physical behavior of numerous of independent carp; (2) carp aggregation is a collective effect of inter-carp and carp-environment interaction; (3) the inter-carp interaction can be derived from the statistical analytics about large-scale observed data. The proposed mathematical model is mainly based on empirical inter-carp force field, whose effect is featured with repulsion, parallel orientation, attraction, out-of-perception zone, and blind. Based on above mathematical model, the aggregation behavior of carp is formulated and preliminary simulation results about the aggregation of small number of carps within simple environment are provided. Further experiment-based validation about the mathematical model will be made in our future work.

  2. Development and verification of an agent-based model of opinion leadership.

    PubMed

    Anderson, Christine A; Titler, Marita G

    2014-09-27

    The use of opinion leaders is a strategy used to speed the process of translating research into practice. Much is still unknown about opinion leader attributes and activities and the context in which they are most effective. Agent-based modeling is a methodological tool that enables demonstration of the interactive and dynamic effects of individuals and their behaviors on other individuals in the environment. The purpose of this study was to develop and test an agent-based model of opinion leadership. The details of the design and verification of the model are presented. The agent-based model was developed by using a software development platform to translate an underlying conceptual model of opinion leadership into a computer model. Individual agent attributes (for example, motives and credibility) and behaviors (seeking or providing an opinion) were specified as variables in the model in the context of a fictitious patient care unit. The verification process was designed to test whether or not the agent-based model was capable of reproducing the conditions of the preliminary conceptual model. The verification methods included iterative programmatic testing ('debugging') and exploratory analysis of simulated data obtained from execution of the model. The simulation tests included a parameter sweep, in which the model input variables were adjusted systematically followed by an individual time series experiment. Statistical analysis of model output for the 288 possible simulation scenarios in the parameter sweep revealed that the agent-based model was performing, consistent with the posited relationships in the underlying model. Nurse opinion leaders act on the strength of their beliefs and as a result, become an opinion resource for their uncertain colleagues, depending on their perceived credibility. Over time, some nurses consistently act as this type of resource and have the potential to emerge as opinion leaders in a context where uncertainty exists. The

  3. Dynamic calibration of agent-based models using data assimilation.

    PubMed

    Ward, Jonathan A; Evans, Andrew J; Malleson, Nicolas S

    2016-04-01

    A widespread approach to investigating the dynamical behaviour of complex social systems is via agent-based models (ABMs). In this paper, we describe how such models can be dynamically calibrated using the ensemble Kalman filter (EnKF), a standard method of data assimilation. Our goal is twofold. First, we want to present the EnKF in a simple setting for the benefit of ABM practitioners who are unfamiliar with it. Second, we want to illustrate to data assimilation experts the value of using such methods in the context of ABMs of complex social systems and the new challenges these types of model present. We work towards these goals within the context of a simple question of practical value: how many people are there in Leeds (or any other major city) right now? We build a hierarchy of exemplar models that we use to demonstrate how to apply the EnKF and calibrate these using open data of footfall counts in Leeds.

  4. Dynamic calibration of agent-based models using data assimilation

    PubMed Central

    Ward, Jonathan A.; Evans, Andrew J.; Malleson, Nicolas S.

    2016-01-01

    A widespread approach to investigating the dynamical behaviour of complex social systems is via agent-based models (ABMs). In this paper, we describe how such models can be dynamically calibrated using the ensemble Kalman filter (EnKF), a standard method of data assimilation. Our goal is twofold. First, we want to present the EnKF in a simple setting for the benefit of ABM practitioners who are unfamiliar with it. Second, we want to illustrate to data assimilation experts the value of using such methods in the context of ABMs of complex social systems and the new challenges these types of model present. We work towards these goals within the context of a simple question of practical value: how many people are there in Leeds (or any other major city) right now? We build a hierarchy of exemplar models that we use to demonstrate how to apply the EnKF and calibrate these using open data of footfall counts in Leeds. PMID:27152214

  5. Fluctuation complexity of agent-based financial time series model by stochastic Potts system

    NASA Astrophysics Data System (ADS)

    Hong, Weijia; Wang, Jun

    2015-03-01

    Financial market is a complex evolved dynamic system with high volatilities and noises, and the modeling and analyzing of financial time series are regarded as the rather challenging tasks in financial research. In this work, by applying the Potts dynamic system, a random agent-based financial time series model is developed in an attempt to uncover the empirical laws in finance, where the Potts model is introduced to imitate the trading interactions among the investing agents. Based on the computer simulation in conjunction with the statistical analysis and the nonlinear analysis, we present numerical research to investigate the fluctuation behaviors of the proposed time series model. Furthermore, in order to get a robust conclusion, we consider the daily returns of Shanghai Composite Index and Shenzhen Component Index, and the comparison analysis of return behaviors between the simulation data and the actual data is exhibited.

  6. Domination and evolution in agent based model of an economy

    NASA Astrophysics Data System (ADS)

    Kazmi, Syed S.

    We introduce Agent Based Model of a pure exchange economy and a simple economy that includes production, consumption and distributions. Markets are described by Edgeworth Exchange in both models. Trades are binary bilateral trades at prices that are set in each trade. We found that the prices converge over time to a value that is not the standard Equilibrium value given by the Walrasian Tattonement fiction. The average price, and the distributions of Wealth, depends on the degree of Domination (persuasive power) we introduced based on differentials in trading "leverage" due to wealth differences. The full economy model is allowed to evolve by replacement of agents that do not survive with agents having random properties. We found that, depending upon the average productivity compared to the average consumption, very different kinds of behavior emerged. The Economy as a whole reaches a steady state by the population adapting to the conditions of productivity and consumption. Correlations develop in a population between what would be for each individual a random assignment of Productivity, Labor power, Wealth, and Preferences. The population adapts to the economic environment by development of these Correlations and without any learning process. We see signs of emerging social structure as a result of necessity of survival.

  7. "Economic microscope": The agent-based model set as an instrument in an economic system research

    NASA Astrophysics Data System (ADS)

    Berg, D. B.; Zvereva, O. M.; Akenov, Serik

    2017-07-01

    To create a valid model of a social or economic system one must consider a lot of parameters, conditions and restrictions. Systems and, consequently, the corresponding models are proved to be very complicated. The problem of such system model engineering can't be solved only with mathematical methods usage. The decision could be found in computer simulation. Simulation does not reject mathematical methods, mathematical expressions could become the foundation for a computer model. In these materials the set of agent-based computer models is under discussion. All the set models simulate productive agents communications, but every model is geared towards the specific goal, and, thus, has its own algorithm and its own peculiarities. It is shown that computer simulation can discover new features of the agents' behavior that can not be obtained by analytical solvation of mathematical equations and thus plays the role of some kind of economic microscope.

  8. Graceful Failure and Societal Resilience Analysis Via Agent-Based Modeling and Simulation

    NASA Astrophysics Data System (ADS)

    Schopf, P. S.; Cioffi-Revilla, C.; Rogers, J. D.; Bassett, J.; Hailegiorgis, A. B.

    2014-12-01

    Agent-based social modeling is opening up new methodologies for the study of societal response to weather and climate hazards, and providing measures of resiliency that can be studied in many contexts, particularly in coupled human and natural-technological systems (CHANTS). Since CHANTS are complex adaptive systems, societal resiliency may or may not occur, depending on dynamics that lack closed form solutions. Agent-based modeling has been shown to provide a viable theoretical and methodological approach for analyzing and understanding disasters and societal resiliency in CHANTS. Our approach advances the science of societal resilience through computational modeling and simulation methods that complement earlier statistical and mathematical approaches. We present three case studies of social dynamics modeling that demonstrate the use of these agent based models. In Central Asia, we exmaine mutltiple ensemble simulations with varying climate statistics to see how droughts and zuds affect populations, transmission of wealth across generations, and the overall structure of the social system. In Eastern Africa, we explore how successive episodes of drought events affect the adaptive capacity of rural households. Human displacement, mainly, rural to urban migration, and livelihood transition particularly from pastoral to farming are observed as rural households interacting dynamically with the biophysical environment and continually adjust their behavior to accommodate changes in climate. In the far north case we demonstrate one of the first successful attempts to model the complete climate-permafrost-infrastructure-societal interaction network as a complex adaptive system/CHANTS implemented as a ``federated'' agent-based model using evolutionary computation. Analysis of population changes resulting from extreme weather across these and other cases provides evidence for the emergence of new steady states and shifting patterns of resilience.

  9. Agent-based modeling to simulate the dengue spread

    NASA Astrophysics Data System (ADS)

    Deng, Chengbin; Tao, Haiyan; Ye, Zhiwei

    2008-10-01

    In this paper, we introduce a novel method ABM in simulating the unique process for the dengue spread. Dengue is an acute infectious disease with a long history of over 200 years. Unlike the diseases that can be transmitted directly from person to person, dengue spreads through a must vector of mosquitoes. There is still no any special effective medicine and vaccine for dengue up till now. The best way to prevent dengue spread is to take precautions beforehand. Thus, it is crucial to detect and study the dynamic process of dengue spread that closely relates to human-environment interactions where Agent-Based Modeling (ABM) effectively works. The model attempts to simulate the dengue spread in a more realistic way in the bottom-up way, and to overcome the limitation of ABM, namely overlooking the influence of geographic and environmental factors. Considering the influence of environment, Aedes aegypti ecology and other epidemiological characteristics of dengue spread, ABM can be regarded as a useful way to simulate the whole process so as to disclose the essence of the evolution of dengue spread.

  10. Agent-based modelling of consumer energy choices

    NASA Astrophysics Data System (ADS)

    Rai, Varun; Henry, Adam Douglas

    2016-06-01

    Strategies to mitigate global climate change should be grounded in a rigorous understanding of energy systems, particularly the factors that drive energy demand. Agent-based modelling (ABM) is a powerful tool for representing the complexities of energy demand, such as social interactions and spatial constraints. Unlike other approaches for modelling energy demand, ABM is not limited to studying perfectly rational agents or to abstracting micro details into system-level equations. Instead, ABM provides the ability to represent behaviours of energy consumers -- such as individual households -- using a range of theories, and to examine how the interaction of heterogeneous agents at the micro-level produces macro outcomes of importance to the global climate, such as the adoption of low-carbon behaviours and technologies over space and time. We provide an overview of ABM work in the area of consumer energy choices, with a focus on identifying specific ways in which ABM can improve understanding of both fundamental scientific and applied aspects of the demand side of energy to aid the design of better policies and programmes. Future research needs for improving the practice of ABM to better understand energy demand are also discussed.

  11. E-laboratories : agent-based modeling of electricity markets.

    SciTech Connect

    North, M.; Conzelmann, G.; Koritarov, V.; Macal, C.; Thimmapuram, P.; Veselka, T.

    2002-05-03

    Electricity markets are complex adaptive systems that operate under a wide range of rules that span a variety of time scales. These rules are imposed both from above by society and below by physics. Many electricity markets are undergoing or are about to undergo a transition from centrally regulated systems to decentralized markets. Furthermore, several electricity markets have recently undergone this transition with extremely unsatisfactory results, most notably in California. These high stakes transitions require the introduction of largely untested regulatory structures. Suitable laboratories that can be used to test regulatory structures before they are applied to real systems are needed. Agent-based models can provide such electronic laboratories or ''e-laboratories.'' To better understand the requirements of an electricity market e-laboratory, a live electricity market simulation was created. This experience helped to shape the development of the Electricity Market Complex Adaptive Systems (EMCAS) model. To explore EMCAS' potential as an e-laboratory, several variations of the live simulation were created. These variations probed the possible effects of changing power plant outages and price setting rules on electricity market prices.

  12. Agent Based Modeling of Human Gut Microbiome Interactions and Perturbations

    PubMed Central

    Shashkova, Tatiana; Popenko, Anna; Tyakht, Alexander; Peskov, Kirill; Kosinsky, Yuri; Bogolubsky, Lev; Raigorodskii, Andrei; Ischenko, Dmitry; Alexeev, Dmitry; Govorun, Vadim

    2016-01-01

    Background Intestinal microbiota plays an important role in the human health. It is involved in the digestion and protects the host against external pathogens. Examination of the intestinal microbiome interactions is required for understanding of the community influence on host health. Studies of the microbiome can provide insight on methods of improving health, including specific clinical procedures for individual microbial community composition modification and microbiota correction by colonizing with new bacterial species or dietary changes. Methodology/Principal Findings In this work we report an agent-based model of interactions between two bacterial species and between species and the gut. The model is based on reactions describing bacterial fermentation of polysaccharides to acetate and propionate and fermentation of acetate to butyrate. Antibiotic treatment was chosen as disturbance factor and used to investigate stability of the system. System recovery after antibiotic treatment was analyzed as dependence on quantity of feedback interactions inside the community, therapy duration and amount of antibiotics. Bacterial species are known to mutate and acquire resistance to the antibiotics. The ability to mutate was considered to be a stochastic process, under this suggestion ratio of sensitive to resistant bacteria was calculated during antibiotic therapy and recovery. Conclusion/Significance The model confirms a hypothesis of feedbacks mechanisms necessity for providing functionality and stability of the system after disturbance. High fraction of bacterial community was shown to mutate during antibiotic treatment, though sensitive strains could become dominating after recovery. The recovery of sensitive strains is explained by fitness cost of the resistance. The model demonstrates not only quantitative dynamics of bacterial species, but also gives an ability to observe the emergent spatial structure and its alteration, depending on various feedback mechanisms

  13. Agent-based modeling of host–pathogen systems: The successes and challenges

    PubMed Central

    Bauer, Amy L.; Beauchemin, Catherine A.A.; Perelson, Alan S.

    2009-01-01

    Agent-based models have been employed to describe numerous processes in immunology. Simulations based on these types of models have been used to enhance our understanding of immunology and disease pathology. We review various agent-based models relevant to host–pathogen systems and discuss their contributions to our understanding of biological processes. We then point out some limitations and challenges of agent-based models and encourage efforts towards reproducibility and model validation. PMID:20161146

  14. An agent-based model of collective emotions in online communities

    NASA Astrophysics Data System (ADS)

    Schweitzer, F.; Garcia, D.

    2010-10-01

    We develop an agent-based framework to model the emergence of collective emotions, which is applied to online communities. Agent’s individual emotions are described by their valence and arousal. Using the concept of Brownian agents, these variables change according to a stochastic dynamics, which also considers the feedback from online communication. Agents generate emotional information, which is stored and distributed in a field modeling the online medium. This field affects the emotional states of agents in a non-linear manner. We derive conditions for the emergence of collective emotions, observable in a bimodal valence distribution. Dependent on a saturated or a superlinear feedback between the information field and the agent’s arousal, we further identify scenarios where collective emotions only appear once or in a repeated manner. The analytical results are illustrated by agent-based computer simulations. Our framework provides testable hypotheses about the emergence of collective emotions, which can be verified by data from online communities.

  15. A Harris-Todaro Agent-Based Model to Rural-Urban Migration

    NASA Astrophysics Data System (ADS)

    Espíndola, Aquino L.; Silveira, Jaylson J.; Penna, T. J. P.

    2006-09-01

    The Harris-Todaro model of the rural-urban migration process is revisited under an agent-based approach. The migration of the workers is interpreted as a process of social learning by imitation, formalized by a computational model. By simulating this model, we observe a transitional dynamics with continuous growth of the urban fraction of overall population toward an equilibrium. Such an equilibrium is characterized by stabilization of rural-urban expected wages differential (generalized Harris-Todaro equilibrium condition), urban concentration and urban unemployment. These classic results obtained originally by Harris and Todaro are emergent properties of our model.

  16. Development of Mechanistic Reasoning and Multilevel Explanations of Ecology in Third Grade Using Agent-Based Models

    ERIC Educational Resources Information Center

    Dickes, Amanda Catherine; Sengupta, Pratim; Farris, Amy Voss; Satabdi, Basu

    2016-01-01

    In this paper, we present a third-grade ecology learning environment that integrates two forms of modeling--embodied modeling and agent-based modeling (ABMs)--through the generation of mathematical representations that are common to both forms of modeling. The term "agent" in the context of ABMs indicates individual computational objects…

  17. Development of Mechanistic Reasoning and Multilevel Explanations of Ecology in Third Grade Using Agent-Based Models

    ERIC Educational Resources Information Center

    Dickes, Amanda Catherine; Sengupta, Pratim; Farris, Amy Voss; Satabdi, Basu

    2016-01-01

    In this paper, we present a third-grade ecology learning environment that integrates two forms of modeling--embodied modeling and agent-based modeling (ABMs)--through the generation of mathematical representations that are common to both forms of modeling. The term "agent" in the context of ABMs indicates individual computational objects…

  18. A Systematic Review of Agent-Based Modelling and Simulation Applications in the Higher Education Domain

    ERIC Educational Resources Information Center

    Gu, X.; Blackmore, K. L.

    2015-01-01

    This paper presents the results of a systematic review of agent-based modelling and simulation (ABMS) applications in the higher education (HE) domain. Agent-based modelling is a "bottom-up" modelling paradigm in which system-level behaviour (macro) is modelled through the behaviour of individual local-level agent interactions (micro).…

  19. A Systematic Review of Agent-Based Modelling and Simulation Applications in the Higher Education Domain

    ERIC Educational Resources Information Center

    Gu, X.; Blackmore, K. L.

    2015-01-01

    This paper presents the results of a systematic review of agent-based modelling and simulation (ABMS) applications in the higher education (HE) domain. Agent-based modelling is a "bottom-up" modelling paradigm in which system-level behaviour (macro) is modelled through the behaviour of individual local-level agent interactions (micro).…

  20. Agent-based computer simulation and sirs: building a bridge between basic science and clinical trials.

    PubMed

    An, G

    2001-10-01

    The management of Systemic Inflammatory Response Syndrome (SIRS)/Multiple Organ Failure (MOF) remains the greatest challenge in the field of critical care. There has been uniform difficulty in translating the results of basic science research into effective therapeutic regimes. We propose that this is due in part to a failure to account for the complex, nonlinear nature of the inflammatory process of which SIRS/MOF represents a disordered state. Attempts to manipulate this process without an understanding of the dynamics of the system may potentially produce unintended consequences. Agent-Based Computer Simulation (ABCS) provides a means to synthesize the information acquired from the linear analysis of basic science into a model that preserves the complexity of the inflammatory system. We have constructed an abstracted version of the inflammatory process using an ABCS that is based at the cellular level. Despite its abstraction, the simulation produces non-linear behavior and reproduces the dynamic structure of the inflammatory response. Furthermore, adjustment of the simulation to model one of the unsuccessful initial anti-inflammatory trials of the 1990's demonstrates the adverse outcome that was observed in those clinical trials. It must be emphasized that the current model is extremely abstract and simplified. However, it is hoped that future ABCSs of sufficient sophistication eventually may provide an important bridging tool to translate basic science discoveries into clinical applications. Creating these simulations will require a large collaborative effort, and it is hoped that this paper will stimulate interest in this form of analysis.

  1. A mathematical framework for agent based models of complex biological networks.

    PubMed

    Hinkelmann, Franziska; Murrugarra, David; Jarrah, Abdul Salam; Laubenbacher, Reinhard

    2011-07-01

    Agent-based modeling and simulation is a useful method to study biological phenomena in a wide range of fields, from molecular biology to ecology. Since there is currently no agreed-upon standard way to specify such models, it is not always easy to use published models. Also, since model descriptions are not usually given in mathematical terms, it is difficult to bring mathematical analysis tools to bear, so that models are typically studied through simulation. In order to address this issue, Grimm et al. proposed a protocol for model specification, the so-called ODD protocol, which provides a standard way to describe models. This paper proposes an addition to the ODD protocol which allows the description of an agent-based model as a dynamical system, which provides access to computational and theoretical tools for its analysis. The mathematical framework is that of algebraic models, that is, time-discrete dynamical systems with algebraic structure. It is shown by way of several examples how this mathematical specification can help with model analysis. This mathematical framework can also accommodate other model types such as Boolean networks and the more general logical models, as well as Petri nets.

  2. Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions

    PubMed Central

    Lawley, Mark A.; Siscovick, David S.; Zhang, Donglan; Pagán, José A.

    2016-01-01

    The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions. PMID:27236380

  3. Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions.

    PubMed

    Li, Yan; Lawley, Mark A; Siscovick, David S; Zhang, Donglan; Pagán, José A

    2016-05-26

    The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions.

  4. Global Critical Materials Markets: An Agent-based Modeling Approach

    SciTech Connect

    Riddle, Matthew E.; Macal, Charles M.; Conzelmann, Guenter; Combs, Todd E.; Bauer, Diana; Fields, Fletcher

    2015-09-01

    As part of efforts to position the United States as a leader in clean energy technology production, the U. S. Department of Energy (DOE) issued two Critical Materials Strategy reports, which assessed 16 materials on the basis of their importance to clean energy development and their supply risk ( U.S. Department of Energy (DOE), 2010 and DOE, 2011). To understand the implications for clean energy of disruptions in supplies of critical materials, it is important to understand supply chain dynamics from mining to final product production. As a case study of critical material supply chains, we focus on the supply of two rare earth metals, neodymium (Nd) and dysprosium (Dy), for permanent magnets used in wind turbines, electric vehicles and other applications. We introduce GCMat, a dynamic agent-based model that includes interacting agents at five supply chain stages consisting of mining, metal refining, magnet production, final product production and demand. Agents throughout the supply chain make pricing, production and inventory management decisions. Deposit developers choose which deposits to develop based on market conditions and detailed data on 57 rare earth deposits. Wind turbine and electric vehicle producers choose from a set of possible production technologies that require different amounts of rare earths. We ran the model under a baseline scenario and four alternative scenarios with different demand and production technology inputs. Model results from 2010 to 2013 fit well with historical data. Projections through 2025 show a number of possible future price, demand, and supply trajectories. For each scenario, we highlight reasons for turning points under market conditions, for differences between Nd and Dy markets, and for differences between scenarios. Because GCMat can model causal dynamics and provide fine-grain representation of agents and their decisions, it provides explanations for turning points under market conditions that are not otherwise

  5. New approaches in agent-based modeling of complex financial systems

    NASA Astrophysics Data System (ADS)

    Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

    2017-12-01

    Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.

  6. Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

    NASA Astrophysics Data System (ADS)

    Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

    2014-09-01

    Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

  7. A Hybrid Sensitivity Analysis Approach for Agent-based Disease Spread Models

    SciTech Connect

    Pullum, Laura L; Cui, Xiaohui

    2012-01-01

    Agent-based models (ABM) have been widely deployed in different fields for studying the collective behavior of large numbers of interacting agents. Of particular interest lately is the application of agent-based and hybrid models to epidemiology, specifically Agent-based Disease Spread Models (ABDSM). Validation (one aspect of the means to achieve dependability) of ABDSM simulation models is extremely important. It ensures that the right model has been built and lends confidence to the use of that model to inform critical decisions. In this report, we describe our preliminary efforts in ABDSM validation by using hybrid model fusion technology.

  8. An agent-based model for domestic water management in Valladolid metropolitan area

    NASA Astrophysics Data System (ADS)

    GaláN, José M.; López-Paredes, Adolfo; Del Olmo, Ricardo

    2009-05-01

    In this work we demonstrate that the combination of agent-based modeling and simulation constitutes a useful methodological approach to dealing with the complexity derived from multiple factors with influence in the domestic water management in emergent metropolitan areas. In particular, we adapt and integrate different social submodels, models of urban dynamics, water consumption, and technological and opinion diffusion, in an agent-based model that is, in turn, linked with a geographic information system. The result is a computational environment that enables simulating and comparing various water demand scenarios. We have parameterized our general model for the metropolitan area of Valladolid (Spain).The model shows the influence of urban dynamics (e.g., intrapopulation movements, residence typology, and changes in the territorial model) and other socio-geographic effects (technological and opinion dynamics) in domestic water demand. The conclusions drawn in this way would have been difficult to obtain using other approaches, such as conventional forecasting methods, given the need to integrate different socioeconomic and geographic aspects in one single model. We illustrate that the described methodology can complement conventional approaches, providing descriptive and formal additional insights into domestic water demand management problems.

  9. Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks.

    PubMed

    Walpole, J; Chappell, J C; Cluceru, J G; Mac Gabhann, F; Bautch, V L; Peirce, S M

    2015-09-01

    Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods.

  10. Agent based reasoning for the non-linear stochastic models of long-range memory

    NASA Astrophysics Data System (ADS)

    Kononovicius, A.; Gontis, V.

    2012-02-01

    We extend Kirman's model by introducing variable event time scale. The proposed flexible time scale is equivalent to the variable trading activity observed in financial markets. Stochastic version of the extended Kirman's agent based model is compared to the non-linear stochastic models of long-range memory in financial markets. The agent based model providing matching macroscopic description serves as a microscopic reasoning of the earlier proposed stochastic model exhibiting power law statistics.

  11. Spatial process and data models : toward integration of agent-based models and GIS.

    SciTech Connect

    Brown, D. G.; North, M. J.; Robinson, D. T.; Riolo, R.; Rand, W.; Decision and Information Sciences; Univ. of Michigan

    2007-10-01

    The use of object-orientation for both spatial data and spatial process models facilitates their integration, which can allow exploration and explanation of spatial-temporal phenomena. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, we identify four key relationships affecting how geographic data (fields and objects) and agent-based process models can interact: identity, causal, temporal and topological. We discuss approaches to implementing tight integration, focusing on a middleware approach that links existing GIS and ABM development platforms, and illustrate the need and approaches with example agent-based models.

  12. Ensuring congruency in multiscale modeling: towards linking agent based and continuum biomechanical models of arterial adaptation.

    PubMed

    Hayenga, Heather N; Thorne, Bryan C; Peirce, Shayn M; Humphrey, Jay D

    2011-11-01

    There is a need to develop multiscale models of vascular adaptations to understand tissue-level manifestations of cellular level mechanisms. Continuum-based biomechanical models are well suited for relating blood pressures and flows to stress-mediated changes in geometry and properties, but less so for describing underlying mechanobiological processes. Discrete stochastic agent-based models are well suited for representing biological processes at a cellular level, but not for describing tissue-level mechanical changes. We present here a conceptually new approach to facilitate the coupling of continuum and agent-based models. Because of ubiquitous limitations in both the tissue- and cell-level data from which one derives constitutive relations for continuum models and rule-sets for agent-based models, we suggest that model verification should enforce congruency across scales. That is, multiscale model parameters initially determined from data sets representing different scales should be refined, when possible, to ensure that common outputs are consistent. Potential advantages of this approach are illustrated by comparing simulated aortic responses to a sustained increase in blood pressure predicted by continuum and agent-based models both before and after instituting a genetic algorithm to refine 16 objectively bounded model parameters. We show that congruency-based parameter refinement not only yielded increased consistency across scales, it also yielded predictions that are closer to in vivo observations.

  13. Reducing the Complexity of an Agent-Based Local Heroin Market Model

    PubMed Central

    Heard, Daniel; Bobashev, Georgiy V.; Morris, Robert J.

    2014-01-01

    This project explores techniques for reducing the complexity of an agent-based model (ABM). The analysis involved a model developed from the ethnographic research of Dr. Lee Hoffer in the Larimer area heroin market, which involved drug users, drug sellers, homeless individuals and police. The authors used statistical techniques to create a reduced version of the original model which maintained simulation fidelity while reducing computational complexity. This involved identifying key summary quantities of individual customer behavior as well as overall market activity and replacing some agents with probability distributions and regressions. The model was then extended to allow external market interventions in the form of police busts. Extensions of this research perspective, as well as its strengths and limitations, are discussed. PMID:25025132

  14. Reducing the complexity of an agent-based local heroin market model.

    PubMed

    Heard, Daniel; Bobashev, Georgiy V; Morris, Robert J

    2014-01-01

    This project explores techniques for reducing the complexity of an agent-based model (ABM). The analysis involved a model developed from the ethnographic research of Dr. Lee Hoffer in the Larimer area heroin market, which involved drug users, drug sellers, homeless individuals and police. The authors used statistical techniques to create a reduced version of the original model which maintained simulation fidelity while reducing computational complexity. This involved identifying key summary quantities of individual customer behavior as well as overall market activity and replacing some agents with probability distributions and regressions. The model was then extended to allow external market interventions in the form of police busts. Extensions of this research perspective, as well as its strengths and limitations, are discussed.

  15. A three-dimensional multi-agent-based model for the evolution of Chagas' disease.

    PubMed

    Galvão, Viviane; Miranda, José Garcia Vivas

    2010-06-01

    A better understanding of Chagas' disease is important because the knowledge about the progression and the participation of the different types of cells in this disease are still lacking. To clarify this system, the kinetics of inflammatory cells and parasite nests was shown in an experiment. Using this experimental data, we have developed a three-dimensional multi-agent-based computational model for the evolution of Chagas' disease. Our model includes five different types of agents: inflammatory cell, fibrosis, cardiomyocyte, fibroblast, and Trypanosoma cruzi. Fibrosis is fixed and the other types of agents can move through the empty space. They move randomly by using the Moore neighborhood. This model reproduces the acute and chronic phases of Chagas' disease and the volume occupied by all different types of cells in the cardiac tissue.

  16. Agent-based model for the h-index - exact solution

    NASA Astrophysics Data System (ADS)

    Żogała-Siudem, Barbara; Siudem, Grzegorz; Cena, Anna; Gagolewski, Marek

    2016-01-01

    Hirsch's h-index is perhaps the most popular citation-based measure of scientific excellence. In 2013, Ionescu and Chopard proposed an agent-based model describing a process for generating publications and citations in an abstract scientific community [G. Ionescu, B. Chopard, Eur. Phys. J. B 86, 426 (2013)]. Within such a framework, one may simulate a scientist's activity, and - by extension - investigate the whole community of researchers. Even though the Ionescu and Chopard model predicts the h-index quite well, the authors provided a solution based solely on simulations. In this paper, we complete their results with exact, analytic formulas. What is more, by considering a simplified version of the Ionescu-Chopard model, we obtained a compact, easy to compute formula for the h-index. The derived approximate and exact solutions are investigated on a simulated and real-world data sets.

  17. Why technical trading may be successful? A lesson from the agent-based modeling

    NASA Astrophysics Data System (ADS)

    Schmidt, Anatoly B.

    2002-01-01

    It is shown using a simple agent-based market dynamics model that if the technical traders are able to affect the market liquidity, their concerted actions can move the market price in the direction favorable to their strategy.

  18. Agent-Based vs. Equation-based Epidemiological Models:A Model Selection Case Study

    SciTech Connect

    Sukumar, Sreenivas R; Nutaro, James J

    2012-01-01

    This paper is motivated by the need to design model validation strategies for epidemiological disease-spread models. We consider both agent-based and equation-based models of pandemic disease spread and study the nuances and complexities one has to consider from the perspective of model validation. For this purpose, we instantiate an equation based model and an agent based model of the 1918 Spanish flu and we leverage data published in the literature for our case- study. We present our observations from the perspective of each implementation and discuss the application of model-selection criteria to compare the risk in choosing one modeling paradigm to another. We conclude with a discussion of our experience and document future ideas for a model validation framework.

  19. Agent-based modeling: Methods and techniques for simulating human systems

    PubMed Central

    Bonabeau, Eric

    2002-01-01

    Agent-based modeling is a powerful simulation modeling technique that has seen a number of applications in the last few years, including applications to real-world business problems. After the basic principles of agent-based simulation are briefly introduced, its four areas of application are discussed by using real-world applications: flow simulation, organizational simulation, market simulation, and diffusion simulation. For each category, one or several business applications are described and analyzed. PMID:12011407

  20. Developing a Conceptual Architecture for a Generalized Agent-based Modeling Environment (GAME)

    DTIC Science & Technology

    2008-03-01

    possible. A conceptual architecture for a generalized agent- based modeling environment (GAME) based upon design principles from OR/MS systems was created...conceptual architecture for a generalized agent-based modeling environment (GAME) based upon design principles from OR/MS systems was created that...handle the event, and subsequently form the relevant plans. One of these plans will be selected, and either pushed to the top of the current

  1. Going beyond the unitary curve: incorporating richer cognition into agent-based water resources models

    NASA Astrophysics Data System (ADS)

    Kock, B. E.

    2008-12-01

    The increased availability and understanding of agent-based modeling technology and techniques provides a unique opportunity for water resources modelers, allowing them to go beyond traditional behavioral approaches from neoclassical economics, and add rich cognition to social-hydrological models. Agent-based models provide for an individual focus, and the easier and more realistic incorporation of learning, memory and other mechanisms for increased cognitive sophistication. We are in an age of global change impacting complex water resources systems, and social responses are increasingly recognized as fundamentally adaptive and emergent. In consideration of this, water resources models and modelers need to better address social dynamics in a manner beyond the capabilities of neoclassical economics theory and practice. However, going beyond the unitary curve requires unique levels of engagement with stakeholders, both to elicit the richer knowledge necessary for structuring and parameterizing agent-based models, but also to make sure such models are appropriately used. With the aim of encouraging epistemological and methodological convergence in the agent-based modeling of water resources, we have developed a water resources-specific cognitive model and an associated collaborative modeling process. Our cognitive model emphasizes efficiency in architecture and operation, and capacity to adapt to different application contexts. We describe a current application of this cognitive model and modeling process in the Arkansas Basin of Colorado. In particular, we highlight the potential benefits of, and challenges to, using more sophisticated cognitive models in agent-based water resources models.

  2. Disaggregation and Refinement of System Dynamics Models via Agent-based Modeling

    SciTech Connect

    Nutaro, James J; Ozmen, Ozgur; Schryver, Jack C

    2014-01-01

    System dynamics models are usually used to investigate aggregate level behavior, but these models can be decomposed into agents that have more realistic individual behaviors. Here we develop a simple model of the STEM workforce to illuminate the impacts that arise from the disaggregation and refinement of system dynamics models via agent-based modeling. Particularly, alteration of Poisson assumptions, adding heterogeneity to decision-making processes of agents, and discrete-time formulation are investigated and their impacts are illustrated. The goal is to demonstrate both the promise and danger of agent-based modeling in the context of a relatively simple model and to delineate the importance of modeling decisions that are often overlooked.

  3. Model-Drive Architecture for Agent-Based Systems

    NASA Technical Reports Server (NTRS)

    Gradanin, Denis; Singh, H. Lally; Bohner, Shawn A.; Hinchey, Michael G.

    2004-01-01

    The Model Driven Architecture (MDA) approach uses a platform-independent model to define system functionality, or requirements, using some specification language. The requirements are then translated to a platform-specific model for implementation. An agent architecture based on the human cognitive model of planning, the Cognitive Agent Architecture (Cougaar) is selected for the implementation platform. The resulting Cougaar MDA prescribes certain kinds of models to be used, how those models may be prepared and the relationships of the different kinds of models. Using the existing Cougaar architecture, the level of application composition is elevated from individual components to domain level model specifications in order to generate software artifacts. The software artifacts generation is based on a metamodel. Each component maps to a UML structured component which is then converted into multiple artifacts: Cougaar/Java code, documentation, and test cases.

  4. Dynamic Exploration of Helicopter Reconnaissance Through Agent-Based Modeling

    DTIC Science & Technology

    2000-09-01

    Multi - Agent System modeling to develop a simulation of tactical helicopter performance while conducting armed reconnaissance. It focuses on creating a model to support planning for the Test and Evaluation phas of the Comanche helicopter acquisition cycle. The model serves as an initial simulation laboratory for scenario planning, requirements forecasting, and platform comparison analyses. The model implements adaptive tactical movement with agent sensory and weaponry system characteristics. Agents are able to determine their movement direction and paths based on

  5. BSim: an agent-based tool for modeling bacterial populations in systems and synthetic biology.

    PubMed

    Gorochowski, Thomas E; Matyjaszkiewicz, Antoni; Todd, Thomas; Oak, Neeraj; Kowalska, Kira; Reid, Stephen; Tsaneva-Atanasova, Krasimira T; Savery, Nigel J; Grierson, Claire S; di Bernardo, Mario

    2012-01-01

    Large-scale collective behaviors such as synchronization and coordination spontaneously arise in many bacterial populations. With systems biology attempting to understand these phenomena, and synthetic biology opening up the possibility of engineering them for our own benefit, there is growing interest in how bacterial populations are best modeled. Here we introduce BSim, a highly flexible agent-based computational tool for analyzing the relationships between single-cell dynamics and population level features. BSim includes reference implementations of many bacterial traits to enable the quick development of new models partially built from existing ones. Unlike existing modeling tools, BSim fully considers spatial aspects of a model allowing for the description of intricate micro-scale structures, enabling the modeling of bacterial behavior in more realistic three-dimensional, complex environments. The new opportunities that BSim opens are illustrated through several diverse examples covering: spatial multicellular computing, modeling complex environments, population dynamics of the lac operon, and the synchronization of genetic oscillators. BSim is open source software that is freely available from http://bsim-bccs.sf.net and distributed under the Open Source Initiative (OSI) recognized MIT license. Developer documentation and a wide range of example simulations are also available from the website. BSim requires Java version 1.6 or higher.

  6. Agent based modeling of the coevolution of hostility and pacifism

    NASA Astrophysics Data System (ADS)

    Dalmagro, Fermin; Jimenez, Juan

    2015-01-01

    We propose a model based on a population of agents whose states represent either hostile or peaceful behavior. Randomly selected pairs of agents interact according to a variation of the Prisoners Dilemma game, and the probabilities that the agents behave aggressively or not are constantly updated by the model so that the agents that remain in the game are those with the highest fitness. We show that the population of agents oscillate between generalized conflict and global peace, without either reaching a stable state. We then use this model to explain some of the emergent behaviors in collective conflicts, by comparing the simulated results with empirical data obtained from social systems. In particular, using public data reports we show how the model precisely reproduces interesting quantitative characteristics of diverse types of armed conflicts, public protests, riots and strikes.

  7. Analytical Tools for Investigating and Modeling Agent-Based Systems

    DTIC Science & Technology

    2005-06-01

    to be high. For example, the binomial distribution can be used to derive the expected number of objects x1 in sample A with a matching object x2 in B...6] and development of models that select attribute estimators based on data characteristics. 7. Acknowledgments We thank Ross Fairgrieve for his...best pre- diction of tomorrow’s stock prices is based on today’s prices (Wooldrige, 2003). 1 If a conventional linear regression model is used to

  8. Deriving effective vaccine allocation strategies for pandemic influenza: Comparison of an agent-based simulation and a compartmental model

    PubMed Central

    Dalgıç, Özden O.; Özaltın, Osman Y.; Ciccotelli, William A.; Erenay, Fatih S.

    2017-01-01

    Individuals are prioritized based on their risk profiles when allocating limited vaccine stocks during an influenza pandemic. Computationally expensive but realistic agent-based simulations and fast but stylized compartmental models are typically used to derive effective vaccine allocation strategies. A detailed comparison of these two approaches, however, is often omitted. We derive age-specific vaccine allocation strategies to mitigate a pandemic influenza outbreak in Seattle by applying derivative-free optimization to an agent-based simulation and also to a compartmental model. We compare the strategies derived by these two approaches under various infection aggressiveness and vaccine coverage scenarios. We observe that both approaches primarily vaccinate school children, however they may allocate the remaining vaccines in different ways. The vaccine allocation strategies derived by using the agent-based simulation are associated with up to 70% decrease in total cost and 34% reduction in the number of infections compared to the strategies derived by using the compartmental model. Nevertheless, the latter approach may still be competitive for very low and/or very high infection aggressiveness. Our results provide insights about potential differences between the vaccine allocation strategies derived by using agent-based simulations and those derived by using compartmental models. PMID:28222123

  9. Physics and financial economics (1776-2014): puzzles, Ising and agent-based models

    NASA Astrophysics Data System (ADS)

    Sornette, Didier

    2014-06-01

    This short review presents a selected history of the mutual fertilization between physics and economics—from Isaac Newton and Adam Smith to the present. The fundamentally different perspectives embraced in theories developed in financial economics compared with physics are dissected with the examples of the volatility smile and of the excess volatility puzzle. The role of the Ising model of phase transitions to model social and financial systems is reviewed, with the concepts of random utilities and the logit model as the analog of the Boltzmann factor in statistical physics. Recent extensions in terms of quantum decision theory are also covered. A wealth of models are discussed briefly that build on the Ising model and generalize it to account for the many stylized facts of financial markets. A summary of the relevance of the Ising model and its extensions is provided to account for financial bubbles and crashes. The review would be incomplete if it did not cover the dynamical field of agent-based models (ABMs), also known as computational economic models, of which the Ising-type models are just special ABM implementations. We formulate the ‘Emerging Intelligence Market Hypothesis’ to reconcile the pervasive presence of ‘noise traders’ with the near efficiency of financial markets. Finally, we note that evolutionary biology, more than physics, is now playing a growing role to inspire models of financial markets.

  10. Physics and financial economics (1776-2014): puzzles, Ising and agent-based models.

    PubMed

    Sornette, Didier

    2014-06-01

    This short review presents a selected history of the mutual fertilization between physics and economics--from Isaac Newton and Adam Smith to the present. The fundamentally different perspectives embraced in theories developed in financial economics compared with physics are dissected with the examples of the volatility smile and of the excess volatility puzzle. The role of the Ising model of phase transitions to model social and financial systems is reviewed, with the concepts of random utilities and the logit model as the analog of the Boltzmann factor in statistical physics. Recent extensions in terms of quantum decision theory are also covered. A wealth of models are discussed briefly that build on the Ising model and generalize it to account for the many stylized facts of financial markets. A summary of the relevance of the Ising model and its extensions is provided to account for financial bubbles and crashes. The review would be incomplete if it did not cover the dynamical field of agent-based models (ABMs), also known as computational economic models, of which the Ising-type models are just special ABM implementations. We formulate the 'Emerging Intelligence Market Hypothesis' to reconcile the pervasive presence of 'noise traders' with the near efficiency of financial markets. Finally, we note that evolutionary biology, more than physics, is now playing a growing role to inspire models of financial markets.

  11. Multi-agent-based Order Book Model of financial markets

    NASA Astrophysics Data System (ADS)

    Preis, T.; Golke, S.; Paul, W.; Schneider, J. J.

    2006-08-01

    We introduce a simple model for simulating financial markets, based on an order book, in which several agents trade one asset at a virtual exchange continuously. For a stationary market the structure of the model, the order flow rates of the different kinds of order types and the used price time priority matching algorithm produce only a diffusive price behavior. We show that a market trend, i.e. an asymmetric order flow of any type, leads to a non-trivial Hurst exponent for the price development, but not to "fat-tailed" return distributions. When one additionally couples the order entry depth to the prevailing trend, also the stylized empirical fact of "fat tails" can be reproduced by our Order Book Model.

  12. Empirical Data Sets for Agent Based Modeling of Crowd Scenarios

    DTIC Science & Technology

    2009-08-06

    Conclusion 2UNCLASSIFIED- Approved for Public Release Crowd Research • Large numbers • Heterogeneous • Individual Actors • Interdependence • Language ... Barriers • Empirical testing is difficult • Simulations require models based on real data, otherwise they are fiction 3UNCLASSIFIED- Approved for

  13. Emergence of heterogeneity in an agent-based model

    NASA Astrophysics Data System (ADS)

    Wan Abdullah, Wan Ahmad Tajuddin

    2003-06-01

    We study an interacting agent model of a game-theoretical economy. The agents play a minority-subsequently-majority game and they learn, using backpropagation networks, to obtain higher payoffs. We study the relevance of heterogeneity to performance, and how heterogeneity emerges.

  14. Statistical properties of agent-based market area model

    NASA Astrophysics Data System (ADS)

    Kuscsik, Zoltán; Horváth, Denis

    One dimensional stylized model taking into account spatial activity of firms with uniformly distributed customers is proposed. The spatial selling area of each firm is defined by a short interval cut out from selling space (large interval). In this represen- tation, the firm size is directly associated with the size of its selling interval.

  15. Developing a multiscale, multi-resolution agent-based brain tumor model by graphics processing units.

    PubMed

    Zhang, Le; Jiang, Beini; Wu, Yukun; Strouthos, Costas; Sun, Phillip Zhe; Su, Jing; Zhou, Xiaobo

    2011-12-16

    Multiscale agent-based modeling (MABM) has been widely used to simulate Glioblastoma Multiforme (GBM) and its progression. At the intracellular level, the MABM approach employs a system of ordinary differential equations to describe quantitatively specific intracellular molecular pathways that determine phenotypic switches among cells (e.g. from migration to proliferation and vice versa). At the intercellular level, MABM describes cell-cell interactions by a discrete module. At the tissue level, partial differential equations are employed to model the diffusion of chemoattractants, which are the input factors of the intracellular molecular pathway. Moreover, multiscale analysis makes it possible to explore the molecules that play important roles in determining the cellular phenotypic switches that in turn drive the whole GBM expansion. However, owing to limited computational resources, MABM is currently a theoretical biological model that uses relatively coarse grids to simulate a few cancer cells in a small slice of brain cancer tissue. In order to improve this theoretical model to simulate and predict actual GBM cancer progression in real time, a graphics processing unit (GPU)-based parallel computing algorithm was developed and combined with the multi-resolution design to speed up the MABM. The simulated results demonstrated that the GPU-based, multi-resolution and multiscale approach can accelerate the previous MABM around 30-fold with relatively fine grids in a large extracellular matrix. Therefore, the new model has great potential for simulating and predicting real-time GBM progression, if real experimental data are incorporated.

  16. Developing a multiscale, multi-resolution agent-based brain tumor model by graphics processing units

    PubMed Central

    2011-01-01

    Multiscale agent-based modeling (MABM) has been widely used to simulate Glioblastoma Multiforme (GBM) and its progression. At the intracellular level, the MABM approach employs a system of ordinary differential equations to describe quantitatively specific intracellular molecular pathways that determine phenotypic switches among cells (e.g. from migration to proliferation and vice versa). At the intercellular level, MABM describes cell-cell interactions by a discrete module. At the tissue level, partial differential equations are employed to model the diffusion of chemoattractants, which are the input factors of the intracellular molecular pathway. Moreover, multiscale analysis makes it possible to explore the molecules that play important roles in determining the cellular phenotypic switches that in turn drive the whole GBM expansion. However, owing to limited computational resources, MABM is currently a theoretical biological model that uses relatively coarse grids to simulate a few cancer cells in a small slice of brain cancer tissue. In order to improve this theoretical model to simulate and predict actual GBM cancer progression in real time, a graphics processing unit (GPU)-based parallel computing algorithm was developed and combined with the multi-resolution design to speed up the MABM. The simulated results demonstrated that the GPU-based, multi-resolution and multiscale approach can accelerate the previous MABM around 30-fold with relatively fine grids in a large extracellular matrix. Therefore, the new model has great potential for simulating and predicting real-time GBM progression, if real experimental data are incorporated. PMID:22176732

  17. Efficient Agent-Based Models for Non-Genomic Evolution

    NASA Technical Reports Server (NTRS)

    Gupta, Nachi; Agogino, Adrian; Tumer, Kagan

    2006-01-01

    Modeling dynamical systems composed of aggregations of primitive proteins is critical to the field of astrobiological science involving early evolutionary structures and the origins of life. Unfortunately traditional non-multi-agent methods either require oversimplified models or are slow to converge to adequate solutions. This paper shows how to address these deficiencies by modeling the protein aggregations through a utility based multi-agent system. In this method each agent controls the properties of a set of proteins assigned to that agent. Some of these properties determine the dynamics of the system, such as the ability for some proteins to join or split other proteins, while additional properties determine the aggregation s fitness as a viable primitive cell. We show that over a wide range of starting conditions, there are mechanisins that allow protein aggregations to achieve high values of overall fitness. In addition through the use of agent-specific utilities that remain aligned with the overall global utility, we are able to reach these conclusions with 50 times fewer learning steps.

  18. Efficient Agent-Based Models for Non-Genomic Evolution

    NASA Technical Reports Server (NTRS)

    Gupta, Nachi; Agogino, Adrian; Tumer, Kagan

    2006-01-01

    Modeling dynamical systems composed of aggregations of primitive proteins is critical to the field of astrobiological science involving early evolutionary structures and the origins of life. Unfortunately traditional non-multi-agent methods either require oversimplified models or are slow to converge to adequate solutions. This paper shows how to address these deficiencies by modeling the protein aggregations through a utility based multi-agent system. In this method each agent controls the properties of a set of proteins assigned to that agent. Some of these properties determine the dynamics of the system, such as the ability for some proteins to join or split other proteins, while additional properties determine the aggregation s fitness as a viable primitive cell. We show that over a wide range of starting conditions, there are mechanisins that allow protein aggregations to achieve high values of overall fitness. In addition through the use of agent-specific utilities that remain aligned with the overall global utility, we are able to reach these conclusions with 50 times fewer learning steps.

  19. Pattern-oriented modeling of agent-based complex systems: Lessons from ecology

    USGS Publications Warehouse

    Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

    2005-01-01

    Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

  20. Pattern-oriented modeling of agent-based complex systems: lessons from ecology.

    PubMed

    Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M; Railsback, Steven F; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L

    2005-11-11

    Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

  1. Agent-Based Knowledge Discovery for Modeling and Simulation

    SciTech Connect

    Haack, Jereme N.; Cowell, Andrew J.; Marshall, Eric J.; Fligg, Alan K.; Gregory, Michelle L.; McGrath, Liam R.

    2009-09-15

    This paper describes an approach to using agent technology to extend the automated discovery mechanism of the Knowledge Encapsulation Framework (KEF). KEF is a suite of tools to enable the linking of knowledge inputs (relevant, domain-specific evidence) to modeling and simulation projects, as well as other domains that require an effective collaborative workspace for knowledge-based tasks. This framework can be used to capture evidence (e.g., trusted material such as journal articles and government reports), discover new evidence (covering both trusted and social media), enable discussions surrounding domain-specific topics and provide automatically generated semantic annotations for improved corpus investigation. The current KEF implementation is presented within a semantic wiki environment, providing a simple but powerful collaborative space for team members to review, annotate, discuss and align evidence with their modeling frameworks. The novelty in this approach lies in the combination of automatically tagged and user-vetted resources, which increases user trust in the environment, leading to ease of adoption for the collaborative environment.

  2. An extensible simulation environment and movement metrics for testing walking behavior in agent-based models

    SciTech Connect

    Paul M. Torrens; Atsushi Nara; Xun Li; Haojie Zhu; William A. Griffin; Scott B. Brown

    2012-01-01

    Human movement is a significant ingredient of many social, environmental, and technical systems, yet the importance of movement is often discounted in considering systems complexity. Movement is commonly abstracted in agent-based modeling (which is perhaps the methodological vehicle for modeling complex systems), despite the influence of movement upon information exchange and adaptation in a system. In particular, agent-based models of urban pedestrians often treat movement in proxy form at the expense of faithfully treating movement behavior with realistic agency. There exists little consensus about which method is appropriate for representing movement in agent-based schemes. In this paper, we examine popularly-used methods to drive movement in agent-based models, first by introducing a methodology that can flexibly handle many representations of movement at many different scales and second, introducing a suite of tools to benchmark agent movement between models and against real-world trajectory data. We find that most popular movement schemes do a relatively poor job of representing movement, but that some schemes may well be 'good enough' for some applications. We also discuss potential avenues for improving the representation of movement in agent-based frameworks.

  3. An Agent-Based Model for Studying Child Maltreatment and Child Maltreatment Prevention

    NASA Astrophysics Data System (ADS)

    Hu, Xiaolin; Puddy, Richard W.

    This paper presents an agent-based model that simulates the dynamics of child maltreatment and child maltreatment prevention. The developed model follows the principles of complex systems science and explicitly models a community and its families with multi-level factors and interconnections across the social ecology. This makes it possible to experiment how different factors and prevention strategies can affect the rate of child maltreatment. We present the background of this work and give an overview of the agent-based model and show some simulation results.

  4. Agent-based modeling of lane discipline in heterogeneous traffic

    NASA Astrophysics Data System (ADS)

    Dailisan, Damian N.; Lim, May T.

    2016-09-01

    Designating lanes for different vehicle types is ideal road safety-wise. Practical considerations, however, require road sharing. Using a modified Nagel-Schreckenberg cellular automata model for two vehicle types (cars and motorcycles), we analyzed the interplay of lane discipline, lane changing, and vehicle density. In the absence of lane changing, the transition between free flow and congested states occurs at a higher vehicle (road occupation) density when the ratio of cars to motorcycles is increased. When lane changing is allowed, the smaller motorcycles tend to fill in unused spaces, until the point when the wider cars effectively block their way at high vehicle densities. When the condition of lane discipline is not imposed, i.e. staying wholly within lane boundaries is not required, further improvement in throughput becomes possible at the cost of required driver attentiveness.

  5. Robust Parameter Design for Agent-Based Simulation Models With Application in a Cultural Geography Model

    DTIC Science & Technology

    2010-06-01

    Ajzen , I. (2006). Theory of planned behavior . Retrieved May 24, 2010, from http://people.umass.edu/aizen/tpb.html Alt, J. K., Jackson, L. A., Hudak...Cultural Geography, Agent-Based Model (ABM), Irregular Warfare (IW), Theory of planned Behavior (TpB), Baysian Belief Nets (BBN), Counterinsurgency...Strategic Multi-layered Assessment SSTR Security, Stability, Transition and Reconstruction Operations TPB Theory of Planned Behavior TRAC-MTRY

  6. Coupled agent-based and finite-element models for predicting scar structure following myocardial infarction.

    PubMed

    Rouillard, Andrew D; Holmes, Jeffrey W

    2014-08-01

    Following myocardial infarction, damaged muscle is gradually replaced by collagenous scar tissue. The structural and mechanical properties of the scar are critical determinants of heart function, as well as the risk of serious post-infarction complications such as infarct rupture, infarct expansion, and progression to dilated heart failure. A number of therapeutic approaches currently under development aim to alter infarct mechanics in order to reduce complications, such as implantation of mechanical restraint devices, polymer injection, and peri-infarct pacing. Because mechanical stimuli regulate scar remodeling, the long-term consequences of therapies that alter infarct mechanics must be carefully considered. Computational models have the potential to greatly improve our ability to understand and predict how such therapies alter heart structure, mechanics, and function over time. Toward this end, we developed a straightforward method for coupling an agent-based model of scar formation to a finite-element model of tissue mechanics, creating a multi-scale model that captures the dynamic interplay between mechanical loading, scar deformation, and scar material properties. The agent-based component of the coupled model predicts how fibroblasts integrate local chemical, structural, and mechanical cues as they deposit and remodel collagen, while the finite-element component predicts local mechanics at any time point given the current collagen fiber structure and applied loads. We used the coupled model to explore the balance between increasing stiffness due to collagen deposition and increasing wall stress due to infarct thinning and left ventricular dilation during the normal time course of healing in myocardial infarcts, as well as the negative feedback between strain anisotropy and the structural anisotropy it promotes in healing scar. The coupled model reproduced the observed evolution of both collagen fiber structure and regional deformation following coronary

  7. A Distributed Platform for Global-Scale Agent-Based Models of Disease Transmission

    PubMed Central

    Parker, Jon; Epstein, Joshua M.

    2013-01-01

    The Global-Scale Agent Model (GSAM) is presented. The GSAM is a high-performance distributed platform for agent-based epidemic modeling capable of simulating a disease outbreak in a population of several billion agents. It is unprecedented in its scale, its speed, and its use of Java. Solutions to multiple challenges inherent in distributing massive agent-based models are presented. Communication, synchronization, and memory usage are among the topics covered in detail. The memory usage discussion is Java specific. However, the communication and synchronization discussions apply broadly. We provide benchmarks illustrating the GSAM’s speed and scalability. PMID:24465120

  8. Building v/s Exploring Models: Comparing Learning of Evolutionary Processes through Agent-based Modeling

    NASA Astrophysics Data System (ADS)

    Wagh, Aditi

    Two strands of work motivate the three studies in this dissertation. Evolutionary change can be viewed as a computational complex system in which a small set of rules operating at the individual level result in different population level outcomes under different conditions. Extensive research has documented students' difficulties with learning about evolutionary change (Rosengren et al., 2012), particularly in terms of levels slippage (Wilensky & Resnick, 1999). Second, though building and using computational models is becoming increasingly common in K-12 science education, we know little about how these two modalities compare. This dissertation adopts agent-based modeling as a representational system to compare these modalities in the conceptual context of micro-evolutionary processes. Drawing on interviews, Study 1 examines middle-school students' productive ways of reasoning about micro-evolutionary processes to find that the specific framing of traits plays a key role in whether slippage explanations are cued. Study 2, which was conducted in 2 schools with about 150 students, forms the crux of the dissertation. It compares learning processes and outcomes when students build their own models or explore a pre-built model. Analysis of Camtasia videos of student pairs reveals that builders' and explorers' ways of accessing rules, and sense-making of observed trends are of a different character. Builders notice rules through available blocks-based primitives, often bypassing their enactment while explorers attend to rules primarily through the enactment. Moreover, builders' sense-making of observed trends is more rule-driven while explorers' is more enactment-driven. Pre and posttests reveal that builders manifest a greater facility with accessing rules, providing explanations manifesting targeted assembly. Explorers use rules to construct explanations manifesting non-targeted assembly. Interviews reveal varying degrees of shifts away from slippage in both

  9. Examining the impact of the walking school bus with an agent-based model.

    PubMed

    Yang, Yong; Diez-Roux, Ana; Evenson, Kelly R; Colabianchi, Natalie

    2014-07-01

    We used an agent-based model to examine the impact of the walking school bus (WSB) on children's active travel to school. We identified a synergistic effect of the WSB with other intervention components such as an educational campaign designed to improve attitudes toward active travel to school. Results suggest that to maximize active travel to school, children should arrive on time at "bus stops" to allow faster WSB walking speeds. We also illustrate how an agent-based model can be used to identify the location of routes maximizing the effects of the WSB on active travel. Agent-based models can be used to examine plausible effects of the WSB on active travel to school under various conditions and to identify ways of implementing the WSB that maximize its effectiveness.

  10. Examining the Impact of the Walking School Bus With an Agent-Based Model

    PubMed Central

    Diez-Roux, Ana; Evenson, Kelly R.; Colabianchi, Natalie

    2014-01-01

    We used an agent-based model to examine the impact of the walking school bus (WSB) on children’s active travel to school. We identified a synergistic effect of the WSB with other intervention components such as an educational campaign designed to improve attitudes toward active travel to school. Results suggest that to maximize active travel to school, children should arrive on time at “bus stops” to allow faster WSB walking speeds. We also illustrate how an agent-based model can be used to identify the location of routes maximizing the effects of the WSB on active travel. Agent-based models can be used to examine plausible effects of the WSB on active travel to school under various conditions and to identify ways of implementing the WSB that maximize its effectiveness. PMID:24832410

  11. Demeter, persephone, and the search for emergence in agent-based models.

    SciTech Connect

    North, M. J.; Howe, T. R.; Collier, N. T.; Vos, J. R.; Decision and Information Sciences; Univ. of Chicago; PantaRei Corp.; Univ. of Illinois

    2006-01-01

    In Greek mythology, the earth goddess Demeter was unable to find her daughter Persephone after Persephone was abducted by Hades, the god of the underworld. Demeter is said to have embarked on a long and frustrating, but ultimately successful, search to find her daughter. Unfortunately, long and frustrating searches are not confined to Greek mythology. In modern times, agent-based modelers often face similar troubles when searching for agents that are to be to be connected to one another and when seeking appropriate target agents while defining agent behaviors. The result is a 'search for emergence' in that many emergent or potentially emergent behaviors in agent-based models of complex adaptive systems either implicitly or explicitly require search functions. This paper considers a new nested querying approach to simplifying such agent-based modeling and multi-agent simulation search problems.

  12. Agent-based modeling supporting the migration of registry systems to grid based architectures.

    PubMed

    Cryer, Martin E; Frey, Lewis

    2009-03-01

    With the increasing age and cost of operation of the existing NCI SEER platform core technologies, such essential resources in the fight against cancer as these will eventually have to be migrated to Grid based systems. In order to model this migration, a simulation is proposed based upon an agent modeling technology. This modeling technique allows for simulation of complex and distributed services provided by a large scale Grid computing platform such as the caBIG(™) project's caGRID. In order to investigate such a migration to a Grid based platform technology, this paper proposes using agent-based modeling simulations to predict the performance of current and Grid configurations of the NCI SEER system integrated with the existing translational opportunities afforded by caGRID. The model illustrates how the use of Grid technology can potentially improve system response time as systems under test are scaled. In modeling SEER nodes accessing multiple registry silos, we show that the performance of SEER applications re-implemented in a Grid native manner exhibits a nearly constant user response time with increasing numbers of distributed registry silos, compared with the current application architecture which exhibits a linear increase in response time for increasing numbers of silos.

  13. Consentaneous Agent-Based and Stochastic Model of the Financial Markets

    PubMed Central

    Gontis, Vygintas; Kononovicius, Aleksejus

    2014-01-01

    We are looking for the agent-based treatment of the financial markets considering necessity to build bridges between microscopic, agent based, and macroscopic, phenomenological modeling. The acknowledgment that agent-based modeling framework, which may provide qualitative and quantitative understanding of the financial markets, is very ambiguous emphasizes the exceptional value of well defined analytically tractable agent systems. Herding as one of the behavior peculiarities considered in the behavioral finance is the main property of the agent interactions we deal with in this contribution. Looking for the consentaneous agent-based and macroscopic approach we combine two origins of the noise: exogenous one, related to the information flow, and endogenous one, arising form the complex stochastic dynamics of agents. As a result we propose a three state agent-based herding model of the financial markets. From this agent-based model we derive a set of stochastic differential equations, which describes underlying macroscopic dynamics of agent population and log price in the financial markets. The obtained solution is then subjected to the exogenous noise, which shapes instantaneous return fluctuations. We test both Gaussian and q-Gaussian noise as a source of the short term fluctuations. The resulting model of the return in the financial markets with the same set of parameters reproduces empirical probability and spectral densities of absolute return observed in New York, Warsaw and NASDAQ OMX Vilnius Stock Exchanges. Our result confirms the prevalent idea in behavioral finance that herding interactions may be dominant over agent rationality and contribute towards bubble formation. PMID:25029364

  14. Consentaneous agent-based and stochastic model of the financial markets.

    PubMed

    Gontis, Vygintas; Kononovicius, Aleksejus

    2014-01-01

    We are looking for the agent-based treatment of the financial markets considering necessity to build bridges between microscopic, agent based, and macroscopic, phenomenological modeling. The acknowledgment that agent-based modeling framework, which may provide qualitative and quantitative understanding of the financial markets, is very ambiguous emphasizes the exceptional value of well defined analytically tractable agent systems. Herding as one of the behavior peculiarities considered in the behavioral finance is the main property of the agent interactions we deal with in this contribution. Looking for the consentaneous agent-based and macroscopic approach we combine two origins of the noise: exogenous one, related to the information flow, and endogenous one, arising form the complex stochastic dynamics of agents. As a result we propose a three state agent-based herding model of the financial markets. From this agent-based model we derive a set of stochastic differential equations, which describes underlying macroscopic dynamics of agent population and log price in the financial markets. The obtained solution is then subjected to the exogenous noise, which shapes instantaneous return fluctuations. We test both Gaussian and q-Gaussian noise as a source of the short term fluctuations. The resulting model of the return in the financial markets with the same set of parameters reproduces empirical probability and spectral densities of absolute return observed in New York, Warsaw and NASDAQ OMX Vilnius Stock Exchanges. Our result confirms the prevalent idea in behavioral finance that herding interactions may be dominant over agent rationality and contribute towards bubble formation.

  15. Mesoscopic Effects in an Agent-Based Bargaining Model in Regular Lattices

    PubMed Central

    Poza, David J.; Santos, José I.; Galán, José M.; López-Paredes, Adolfo

    2011-01-01

    The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the multiagent bargaining model by Axtell, Epstein and Young [1] modifying the assumption of global interaction. Each agent is endowed with a memory and plays the best reply against the opponent's most frequent demand. We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can lead to new persistent regimes different from those found in previous research. In particular, community structure in the intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the hindering diffusion effect of fluctuating agents at their borders. PMID:21408019

  16. Lapse of time effects on tax evasion in an agent-based econophysics model

    NASA Astrophysics Data System (ADS)

    Seibold, Götz; Pickhardt, Michael

    2013-05-01

    We investigate an inhomogeneous Ising model in the context of tax evasion dynamics where different types of agents are parameterized via local temperatures and magnetic fields. In particular, we analyze the impact of lapse of time effects (i.e. backauditing) and endogenously determined penalty rates on tax compliance. Both features contribute to a microfoundation of agent-based econophysics models of tax evasion.

  17. Understanding Group/Party Affiliation Using Social Networks and Agent-Based Modeling

    NASA Technical Reports Server (NTRS)

    Campbell, Kenyth

    2012-01-01

    The dynamics of group affiliation and group dispersion is a concept that is most often studied in order for political candidates to better understand the most efficient way to conduct their campaigns. While political campaigning in the United States is a very hot topic that most politicians analyze and study, the concept of group/party affiliation presents its own area of study that producers very interesting results. One tool for examining party affiliation on a large scale is agent-based modeling (ABM), a paradigm in the modeling and simulation (M&S) field perfectly suited for aggregating individual behaviors to observe large swaths of a population. For this study agent based modeling was used in order to look at a community of agents and determine what factors can affect the group/party affiliation patterns that are present. In the agent-based model that was used for this experiment many factors were present but two main factors were used to determine the results. The results of this study show that it is possible to use agent-based modeling to explore group/party affiliation and construct a model that can mimic real world events. More importantly, the model in the study allows for the results found in a smaller community to be translated into larger experiments to determine if the results will remain present on a much larger scale.

  18. Data-driven agent-based modeling, with application to rooftop solar adoption

    DOE PAGES

    Zhang, Haifeng; Vorobeychik, Yevgeniy; Letchford, Joshua; ...

    2016-01-25

    Agent-based modeling is commonly used for studying complex system properties emergent from interactions among many agents. We present a novel data-driven agent-based modeling framework applied to forecasting individual and aggregate residential rooftop solar adoption in San Diego county. Our first step is to learn a model of individual agent behavior from combined data of individual adoption characteristics and property assessment. We then construct an agent-based simulation with the learned model embedded in artificial agents, and proceed to validate it using a holdout sequence of collective adoption decisions. We demonstrate that the resulting agent-based model successfully forecasts solar adoption trends andmore » provides a meaningful quantification of uncertainty about its predictions. We utilize our model to optimize two classes of policies aimed at spurring solar adoption: one that subsidizes the cost of adoption, and another that gives away free systems to low-income house- holds. We find that the optimal policies derived for the latter class are significantly more efficacious, whereas the policies similar to the current California Solar Initiative incentive scheme appear to have a limited impact on overall adoption trends.« less

  19. Data-driven agent-based modeling, with application to rooftop solar adoption

    SciTech Connect

    Zhang, Haifeng; Vorobeychik, Yevgeniy; Letchford, Joshua; Lakkaraju, Kiran

    2016-01-25

    Agent-based modeling is commonly used for studying complex system properties emergent from interactions among many agents. We present a novel data-driven agent-based modeling framework applied to forecasting individual and aggregate residential rooftop solar adoption in San Diego county. Our first step is to learn a model of individual agent behavior from combined data of individual adoption characteristics and property assessment. We then construct an agent-based simulation with the learned model embedded in artificial agents, and proceed to validate it using a holdout sequence of collective adoption decisions. We demonstrate that the resulting agent-based model successfully forecasts solar adoption trends and provides a meaningful quantification of uncertainty about its predictions. We utilize our model to optimize two classes of policies aimed at spurring solar adoption: one that subsidizes the cost of adoption, and another that gives away free systems to low-income house- holds. We find that the optimal policies derived for the latter class are significantly more efficacious, whereas the policies similar to the current California Solar Initiative incentive scheme appear to have a limited impact on overall adoption trends.

  20. Agent-based modeling as a tool for program design and evaluation.

    PubMed

    Lawlor, Jennifer A; McGirr, Sara

    2017-12-01

    Recently, systems thinking and systems science approaches have gained popularity in the field of evaluation; however, there has been relatively little exploration of how evaluators could use quantitative tools to assist in the implementation of systems approaches therein. The purpose of this paper is to explore potential uses of one such quantitative tool, agent-based modeling, in evaluation practice. To this end, we define agent-based modeling and offer potential uses for it in typical evaluation activities, including: engaging stakeholders, selecting an intervention, modeling program theory, setting performance targets, and interpreting evaluation results. We provide demonstrative examples from published agent-based modeling efforts both inside and outside the field of evaluation for each of the evaluative activities discussed. We further describe potential pitfalls of this tool and offer cautions for evaluators who may chose to implement it in their practice. Finally, the article concludes with a discussion of the future of agent-based modeling in evaluation practice and a call for more formal exploration of this tool as well as other approaches to simulation modeling in the field. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Coevolution in management fashion: an agent-based model of consultant-driven innovation.

    PubMed

    Strang, David; David, Robert J; Akhlaghpour, Saeed

    2014-07-01

    The rise of management consultancy has been accompanied by increasingly marked faddish cycles in management techniques, but the mechanisms that underlie this relationship are not well understood. The authors develop a simple agent-based framework that models innovation adoption and abandonment on both the supply and demand sides. In opposition to conceptions of consultants as rhetorical wizards who engineer waves of management fashion, firms and consultants are treated as boundedly rational actors who chase the secrets of success by mimicking their highest-performing peers. Computational experiments demonstrate that consultant-driven versions of this dynamic in which the outcomes of firms are strongly conditioned by their choice of consultant are robustly faddish. The invasion of boom markets by low-quality consultants undercuts popular innovations while simultaneously restarting the fashion cycle by prompting the flight of high-quality consultants into less densely occupied niches. Computational experiments also indicate conditions involving consultant mobility, aspiration levels, mimic probabilities, and client-provider matching that attenuate faddishness.

  2. Agent based modeling of blood coagulation system: implementation using a GPU based high speed framework.

    PubMed

    Chen, Wenan; Ward, Kevin; Li, Qi; Kecman, Vojislav; Najarian, Kayvan; Menke, Nathan

    2011-01-01

    The coagulation and fibrinolytic systems are complex, inter-connected biological systems with major physiological roles. The complex, nonlinear multi-point relationships between the molecular and cellular constituents of two systems render a comprehensive and simultaneous study of the system at the microscopic and macroscopic level a significant challenge. We have created an Agent Based Modeling and Simulation (ABMS) approach for simulating these complex interactions. As the scale of agents increase, the time complexity and cost of the resulting simulations presents a significant challenge. As such, in this paper, we also present a high-speed framework for the coagulation simulation utilizing the computing power of graphics processing units (GPU). For comparison, we also implemented the simulations in NetLogo, Repast, and a direct C version. As our experiments demonstrate, the computational speed of the GPU implementation of the million-level scale of agents is over 10 times faster versus the C version, over 100 times faster versus the Repast version and over 300 times faster versus the NetLogo simulation.

  3. Synthesized Population Databases: A US Geospatial Database for Agent-Based Models.

    PubMed

    Wheaton, William D; Cajka, James C; Chasteen, Bernadette M; Wagener, Diane K; Cooley, Philip C; Ganapathi, Laxminarayana; Roberts, Douglas J; Allpress, Justine L

    2009-05-01

    Agent-based models simulate large-scale social systems. They assign behaviors and activities to "agents" (individuals) within the population being modeled and then allow the agents to interact with the environment and each other in complex simulations. Agent-based models are frequently used to simulate infectious disease outbreaks, among other uses.RTI used and extended an iterative proportional fitting method to generate a synthesized, geospatially explicit, human agent database that represents the US population in the 50 states and the District of Columbia in the year 2000. Each agent is assigned to a household; other agents make up the household occupants.For this database, RTI developed the methods for generating synthesized households and personsassigning agents to schools and workplaces so that complex interactions among agents as they go about their daily activities can be taken into accountgenerating synthesized human agents who occupy group quarters (military bases, college dormitories, prisons, nursing homes).In this report, we describe both the methods used to generate the synthesized population database and the final data structure and data content of the database. This information will provide researchers with the information they need to use the database in developing agent-based models.Portions of the synthesized agent database are available to any user upon request. RTI will extract a portion (a county, region, or state) of the database for users who wish to use this database in their own agent-based models.

  4. Hybrid agent-based model for quantitative in-silico cell-free protein synthesis.

    PubMed

    Semenchenko, Anton; Oliveira, Guilherme; Atman, A P F

    2016-12-01

    An advanced vision of the mRNA translation is presented through a hybrid modeling approach. The dynamics of the polysome formation was investigated by computer simulation that combined agent-based model and fine-grained Markov chain representation of the chemical kinetics. This approach allowed for the investigation of the polysome dynamics under non-steady-state and non-continuum conditions. The model is validated by the quantitative comparison of the simulation results and Luciferase protein production in cell-free system, as well as by testing of the hypothesis regarding the two possible mechanisms of the Edeine antibiotic. Calculation of the Hurst exponent demonstrated a relationship between the microscopic properties of amino acid elongation and the fractal dimension of the translation duration time series. The temporal properties of the amino acid elongation have indicated an anti-persistent behavior under low mRNA occupancy and evinced the appearance of long range interactions within the mRNA-ribosome system for high ribosome density. The dynamic and temporal characteristics of the polysomal system presented here can have a direct impact on the studies of the co-translation protein folding and provide a validated platform for cell-free system studies.

  5. An Observation-Driven Agent-Based Modeling and Analysis Framework for C. elegans Embryogenesis

    PubMed Central

    Wang, Zi; Ramsey, Benjamin J.; Wang, Dali; Wong, Kwai; Li, Husheng; Wang, Eric; Bao, Zhirong

    2016-01-01

    With cutting-edge live microscopy and image analysis, biologists can now systematically track individual cells in complex tissues and quantify cellular behavior over extended time windows. Computational approaches that utilize the systematic and quantitative data are needed to understand how cells interact in vivo to give rise to the different cell types and 3D morphology of tissues. An agent-based, minimum descriptive modeling and analysis framework is presented in this paper to study C. elegans embryogenesis. The framework is designed to incorporate the large amounts of experimental observations on cellular behavior and reserve data structures/interfaces that allow regulatory mechanisms to be added as more insights are gained. Observed cellular behaviors are organized into lineage identity, timing and direction of cell division, and path of cell movement. The framework also includes global parameters such as the eggshell and a clock. Division and movement behaviors are driven by statistical models of the observations. Data structures/interfaces are reserved for gene list, cell-cell interaction, cell fate and landscape, and other global parameters until the descriptive model is replaced by a regulatory mechanism. This approach provides a framework to handle the ongoing experiments of single-cell analysis of complex tissues where mechanistic insights lag data collection and need to be validated on complex observations. PMID:27851808

  6. An Observation-Driven Agent-Based Modeling and Analysis Framework for C. elegans Embryogenesis.

    PubMed

    Wang, Zi; Ramsey, Benjamin J; Wang, Dali; Wong, Kwai; Li, Husheng; Wang, Eric; Bao, Zhirong

    2016-01-01

    With cutting-edge live microscopy and image analysis, biologists can now systematically track individual cells in complex tissues and quantify cellular behavior over extended time windows. Computational approaches that utilize the systematic and quantitative data are needed to understand how cells interact in vivo to give rise to the different cell types and 3D morphology of tissues. An agent-based, minimum descriptive modeling and analysis framework is presented in this paper to study C. elegans embryogenesis. The framework is designed to incorporate the large amounts of experimental observations on cellular behavior and reserve data structures/interfaces that allow regulatory mechanisms to be added as more insights are gained. Observed cellular behaviors are organized into lineage identity, timing and direction of cell division, and path of cell movement. The framework also includes global parameters such as the eggshell and a clock. Division and movement behaviors are driven by statistical models of the observations. Data structures/interfaces are reserved for gene list, cell-cell interaction, cell fate and landscape, and other global parameters until the descriptive model is replaced by a regulatory mechanism. This approach provides a framework to handle the ongoing experiments of single-cell analysis of complex tissues where mechanistic insights lag data collection and need to be validated on complex observations.

  7. Towards strength and stability : agent-based modeling of infrastructure markets.

    SciTech Connect

    North, M. J.; Decision and Information Sciences

    2001-01-01

    Complex Adaptive Systems (CASs) can be applied to investigate complex infrastructures and infrastructure interdependencies. Agent-based modeling (ABM) is a new CAS-based approach to the construction of models. The CAS agents within the Spot Market Agent Research Tool (SMART) and Flexible Agent Simulation Toolkit (FAST) ABMs allow investigation of the electric power infrastructure, the natural gas infrastructure, and their interdependencies. The Swarm-based SMART models use sets of agents and interconnections to represent electric power and natural gas systems. A prototype virtual reality (VR) interface has also been constructed for a version of the SMART model. This tool is intended to explore the use of advanced interactive three-dimensional visualization in agent-based modeling. The Java-based FAST model is currently under construction. FAST is a complete redesign of the SMART models that includes improvements in the modeling environment, model detail, and representational fidelity. Developing ABMs is difficult but can be rewarding.

  8. Linking agent-based models and stochastic models of financial markets

    PubMed Central

    Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H. Eugene

    2012-01-01

    It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that “fat” tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting. PMID:22586086

  9. Linking agent-based models and stochastic models of financial markets.

    PubMed

    Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H Eugene

    2012-05-29

    It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that "fat" tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting.

  10. Comparing stochastic differential equations and agent-based modelling and simulation for early-stage cancer.

    PubMed

    Figueredo, Grazziela P; Siebers, Peer-Olaf; Owen, Markus R; Reps, Jenna; Aickelin, Uwe

    2014-01-01

    There is great potential to be explored regarding the use of agent-based modelling and simulation as an alternative paradigm to investigate early-stage cancer interactions with the immune system. It does not suffer from some limitations of ordinary differential equation models, such as the lack of stochasticity, representation of individual behaviours rather than aggregates and individual memory. In this paper we investigate the potential contribution of agent-based modelling and simulation when contrasted with stochastic versions of ODE models using early-stage cancer examples. We seek answers to the following questions: (1) Does this new stochastic formulation produce similar results to the agent-based version? (2) Can these methods be used interchangeably? (3) Do agent-based models outcomes reveal any benefit when compared to the Gillespie results? To answer these research questions we investigate three well-established mathematical models describing interactions between tumour cells and immune elements. These case studies were re-conceptualised under an agent-based perspective and also converted to the Gillespie algorithm formulation. Our interest in this work, therefore, is to establish a methodological discussion regarding the usability of different simulation approaches, rather than provide further biological insights into the investigated case studies. Our results show that it is possible to obtain equivalent models that implement the same mechanisms; however, the incapacity of the Gillespie algorithm to retain individual memory of past events affects the similarity of some results. Furthermore, the emergent behaviour of ABMS produces extra patters of behaviour in the system, which was not obtained by the Gillespie algorithm.

  11. Formalizing the Role of Agent-Based Modeling in Causal Inference and Epidemiology

    PubMed Central

    Marshall, Brandon D. L.; Galea, Sandro

    2015-01-01

    Calls for the adoption of complex systems approaches, including agent-based modeling, in the field of epidemiology have largely centered on the potential for such methods to examine complex disease etiologies, which are characterized by feedback behavior, interference, threshold dynamics, and multiple interacting causal effects. However, considerable theoretical and practical issues impede the capacity of agent-based methods to examine and evaluate causal effects and thus illuminate new areas for intervention. We build on this work by describing how agent-based models can be used to simulate counterfactual outcomes in the presence of complexity. We show that these models are of particular utility when the hypothesized causal mechanisms exhibit a high degree of interdependence between multiple causal effects and when interference (i.e., one person's exposure affects the outcome of others) is present and of intrinsic scientific interest. Although not without challenges, agent-based modeling (and complex systems methods broadly) represent a promising novel approach to identify and evaluate complex causal effects, and they are thus well suited to complement other modern epidemiologic methods of etiologic inquiry. PMID:25480821

  12. Formalizing the role of agent-based modeling in causal inference and epidemiology.

    PubMed

    Marshall, Brandon D L; Galea, Sandro

    2015-01-15

    Calls for the adoption of complex systems approaches, including agent-based modeling, in the field of epidemiology have largely centered on the potential for such methods to examine complex disease etiologies, which are characterized by feedback behavior, interference, threshold dynamics, and multiple interacting causal effects. However, considerable theoretical and practical issues impede the capacity of agent-based methods to examine and evaluate causal effects and thus illuminate new areas for intervention. We build on this work by describing how agent-based models can be used to simulate counterfactual outcomes in the presence of complexity. We show that these models are of particular utility when the hypothesized causal mechanisms exhibit a high degree of interdependence between multiple causal effects and when interference (i.e., one person's exposure affects the outcome of others) is present and of intrinsic scientific interest. Although not without challenges, agent-based modeling (and complex systems methods broadly) represent a promising novel approach to identify and evaluate complex causal effects, and they are thus well suited to complement other modern epidemiologic methods of etiologic inquiry.

  13. Agent-Based Models and Optimal Control in Biology: A Discrete Approach

    DTIC Science & Technology

    2012-01-01

    where more details can be found. The focus is on the optimization of cancer chemotherapy, taking into account certain immunological activity. The...Mathematical formalism for agent-based modeling. In R.A. Meyers, editor, Encyclopedia of Complexity and Systems Science, pages 160–176. Springer, 2009

  14. An agent-based model of leukocyte transendothelial migration during atherogenesis

    PubMed Central

    Bhui, Rita; Hayenga, Heather N.

    2017-01-01

    A vast amount of work has been dedicated to the effects of hemodynamics and cytokines on leukocyte adhesion and trans-endothelial migration (TEM) and subsequent accumulation of leukocyte-derived foam cells in the artery wall. However, a comprehensive mechanobiological model to capture these spatiotemporal events and predict the growth and remodeling of an atherosclerotic artery is still lacking. Here, we present a multiscale model of leukocyte TEM and plaque evolution in the left anterior descending (LAD) coronary artery. The approach integrates cellular behaviors via agent-based modeling (ABM) and hemodynamic effects via computational fluid dynamics (CFD). In this computational framework, the ABM implements the diffusion kinetics of key biological proteins, namely Low Density Lipoprotein (LDL), Tissue Necrosis Factor alpha (TNF-α), Interlukin-10 (IL-10) and Interlukin-1 beta (IL-1β), to predict chemotactic driven leukocyte migration into and within the artery wall. The ABM also considers wall shear stress (WSS) dependent leukocyte TEM and compensatory arterial remodeling obeying Glagov’s phenomenon. Interestingly, using fully developed steady blood flow does not result in a representative number of leukocyte TEM as compared to pulsatile flow, whereas passing WSS at peak systole of the pulsatile flow waveform does. Moreover, using the model, we have found leukocyte TEM increases monotonically with decreases in luminal volume. At critical plaque shapes the WSS changes rapidly resulting in sudden increases in leukocyte TEM suggesting lumen volumes that will give rise to rapid plaque growth rates if left untreated. Overall this multi-scale and multi-physics approach appropriately captures and integrates the spatiotemporal events occurring at the cellular level in order to predict leukocyte transmigration and plaque evolution. PMID:28542193

  15. Modeling the Information Age Combat Model: An Agent-Based Simulation of Network Centric Operations

    NASA Technical Reports Server (NTRS)

    Deller, Sean; Rabadi, Ghaith A.; Bell, Michael I.; Bowling, Shannon R.; Tolk, Andreas

    2010-01-01

    The Information Age Combat Model (IACM) was introduced by Cares in 2005 to contribute to the development of an understanding of the influence of connectivity on force effectiveness that can eventually lead to quantitative prediction and guidelines for design and employment. The structure of the IACM makes it clear that the Perron-Frobenius Eigenvalue is a quantifiable metric with which to measure the organization of a networked force. The results of recent experiments presented in Deller, et aI., (2009) indicate that the value of the Perron-Frobenius Eigenvalue is a significant measurement of the performance of an Information Age combat force. This was accomplished through the innovative use of an agent-based simulation to model the IACM and represents an initial contribution towards a new generation of combat models that are net-centric instead of using the current platform-centric approach. This paper describes the intent, challenges, design, and initial results of this agent-based simulation model.

  16. Agent-based model for rural-urban migration: A dynamic consideration

    NASA Astrophysics Data System (ADS)

    Cai, Ning; Ma, Hai-Ying; Khan, M. Junaid

    2015-10-01

    This paper develops a dynamic agent-based model for rural-urban migration, based on the previous relevant works. The model conforms to the typical dynamic linear multi-agent systems model concerned extensively in systems science, in which the communication network is formulated as a digraph. Simulations reveal that consensus of certain variable could be harmful to the overall stability and should be avoided.

  17. Equation-free analysis of agent-based models and systematic parameter determination

    NASA Astrophysics Data System (ADS)

    Thomas, Spencer A.; Lloyd, David J. B.; Skeldon, Anne C.

    2016-12-01

    Agent based models (ABM)s are increasingly used in social science, economics, mathematics, biology and computer science to describe time dependent systems in circumstances where a description in terms of equations is difficult. Yet few tools are currently available for the systematic analysis of ABM behaviour. Numerical continuation and bifurcation analysis is a well-established tool for the study of deterministic systems. Recently, equation-free (EF) methods have been developed to extend numerical continuation techniques to systems where the dynamics are described at a microscopic scale and continuation of a macroscopic property of the system is considered. To date, the practical use of EF methods has been limited by; (1) the over-head of application-specific implementation; (2) the laborious configuration of problem-specific parameters; and (3) large ensemble sizes (potentially) leading to computationally restrictive run-times. In this paper we address these issues with our tool for the EF continuation of stochastic systems, which includes algorithms to systematically configuration problem specific parameters and enhance robustness to noise. Our tool is generic and can be applied to any 'black-box' simulator and determines the essential EF parameters prior to EF analysis. Robustness is significantly improved using our convergence-constraint with a corrector-repeat (C3R) method. This algorithm automatically detects outliers based on the dynamics of the underlying system enabling both an order of magnitude reduction in ensemble size and continuation of systems at much higher levels of noise than classical approaches. We demonstrate our method with application to several ABM models, revealing parameter dependence, bifurcation and stability analysis of these complex systems giving a deep understanding of the dynamical behaviour of the models in a way that is not otherwise easily obtainable. In each case we demonstrate our systematic parameter determination stage for

  18. The comparison of the use of holonic and agent-based methods in modelling of manufacturing systems

    NASA Astrophysics Data System (ADS)

    Foit, K.; Banaś, W.; Gwiazda, A.; Hryniewicz, P.

    2017-08-01

    The rapid evolution in the field of industrial automation and manufacturing is often called the 4th Industry Revolution. Worldwide availability of the internet access contributes to the competition between manufacturers, gives the opportunity for buying materials, parts and for creating the partnership networks, like cloud manufacturing, grid manufacturing (MGrid), virtual enterprises etc. The effect of the industry evolution is the need to search for new solutions in the field of manufacturing systems modelling and simulation. During the last decade researchers have developed the agent-based approach of modelling. This methodology have been taken from the computer science, but was adapted to the philosophy of industrial automation and robotization. The operation of the agent-based system depends on the simultaneous acting of different agents that may have different roles. On the other hand, there is the holon-based approach that uses the structures created by holons. It differs from the agent-based structure in some aspects, while the other ones are quite similar in both methodologies. The aim of this paper is to present the both methodologies and discuss the similarities and the differences. This may could help to select the optimal method of modelling, according to the considered problem and software resources.

  19. An Agent-Based Model of New Venture Creation: Conceptual Design for Simulating Entrepreneurship

    NASA Technical Reports Server (NTRS)

    Provance, Mike; Collins, Andrew; Carayannis, Elias

    2012-01-01

    There is a growing debate over the means by which regions can foster the growth of entrepreneurial activity in order to stimulate recovery and growth of their economies. On one side, agglomeration theory suggests the regions grow because of strong clusters that foster knowledge spillover locally; on the other side, the entrepreneurial action camp argues that innovative business models are generated by entrepreneurs with unique market perspectives who draw on knowledge from more distant domains. We will show you the design for a novel agent-based model of new venture creation that will demonstrate the relationship between agglomeration and action. The primary focus of this model is information exchange as the medium for these agent interactions. Our modeling and simulation study proposes to reveal interesting relationships in these perspectives, offer a foundation on which these disparate theories from economics and sociology can find common ground, and expand the use of agent-based modeling into entrepreneurship research.

  20. Agent Based Modelling Helps in Understanding the Rules by Which Fibroblasts Support Keratinocyte Colony Formation

    PubMed Central

    Sun, Tao; McMinn, Phil; Holcombe, Mike; Smallwood, Rod; MacNeil, Sheila

    2008-01-01

    Background Autologous keratincoytes are routinely expanded using irradiated mouse fibroblasts and bovine serum for clinical use. With growing concerns about the safety of these xenobiotic materials, it is desirable to culture keratinocytes in media without animal derived products. An improved understanding of epithelial/mesenchymal interactions could assist in this. Methodology/Principal Findings A keratincyte/fibroblast o-culture model was developed by extending an agent-based keratinocyte colony formation model to include the response of keratinocytes to both fibroblasts and serum. The model was validated by comparison of the in virtuo and in vitro multicellular behaviour of keratinocytes and fibroblasts in single and co-culture in Greens medium. To test the robustness of the model, several properties of the fibroblasts were changed to investigate their influence on the multicellular morphogenesis of keratinocyes and fibroblasts. The model was then used to generate hypotheses to explore the interactions of both proliferative and growth arrested fibroblasts with keratinocytes. The key predictions arising from the model which were confirmed by in vitro experiments were that 1) the ratio of fibroblasts to keratinocytes would critically influence keratinocyte colony expansion, 2) this ratio needed to be optimum at the beginning of the co-culture, 3) proliferative fibroblasts would be more effective than irradiated cells in expanding keratinocytes and 4) in the presence of an adequate number of fibroblasts, keratinocyte expansion would be independent of serum. Conclusions A closely associated computational and biological approach is a powerful tool for understanding complex biological systems such as the interactions between keratinocytes and fibroblasts. The key outcome of this study is the finding that the early addition of a critical ratio of proliferative fibroblasts can give rapid keratinocyte expansion without the use of irradiated mouse fibroblasts and bovine

  1. An agent-based model of signal transduction in bacterial chemotaxis.

    PubMed

    Miller, Jameson; Parker, Miles; Bourret, Robert B; Giddings, Morgan C

    2010-05-13

    We report the application of agent-based modeling to examine the signal transduction network and receptor arrays for chemotaxis in Escherichia coli, which are responsible for regulating swimming behavior in response to environmental stimuli. Agent-based modeling is a stochastic and bottom-up approach, where individual components of the modeled system are explicitly represented, and bulk properties emerge from their movement and interactions. We present the Chemoscape model: a collection of agents representing both fixed membrane-embedded and mobile cytoplasmic proteins, each governed by a set of rules representing knowledge or hypotheses about their function. When the agents were placed in a simulated cellular space and then allowed to move and interact stochastically, the model exhibited many properties similar to the biological system including adaptation, high signal gain, and wide dynamic range. We found the agent based modeling approach to be both powerful and intuitive for testing hypotheses about biological properties such as self-assembly, the non-linear dynamics that occur through cooperative protein interactions, and non-uniform distributions of proteins in the cell. We applied the model to explore the role of receptor type, geometry and cooperativity in the signal gain and dynamic range of the chemotactic response to environmental stimuli. The model provided substantial qualitative evidence that the dynamic range of chemotactic response can be traced to both the heterogeneity of receptor types present, and the modulation of their cooperativity by their methylation state.

  2. Electricity Market Games: How Agent-Based Modeling Can Help under High Penetrations of Variable Generation

    SciTech Connect

    Gallo, Giulia

    2016-03-01

    Integrating increasingly high levels of variable generation in U.S. electricity markets requires addressing not only power system and grid modeling challenges but also an understanding of how market participants react and adapt to them. Key elements of current and future wholesale power markets can be modeled using an agent-based approach, which may prove to be a useful paradigm for researchers studying and planning for power systems of the future.

  3. Study of simple land battles using agent-based modeling: Strategy and emergent phenomena

    NASA Astrophysics Data System (ADS)

    Westley, Alexandra; de Meglio, Nicholas; Hager, Rebecca; Mok, Jorge Wu; Shanahan, Linda; Sen, Surajit

    2017-04-01

    In this paper, we expand upon our recent studies of an agent-based model of a battle between an intelligent army and an insurgent army to explore the role of modifying strategy according to the state of the battle (adaptive strategy) on battle outcomes. This model leads to surprising complexity and rich possibilities in battle outcomes, especially in battles between two well-matched sides. We contend that the use of adaptive strategies may be effective in winning battles.

  4. Agent-based simulation of building evacuation using a grid graph-based model

    NASA Astrophysics Data System (ADS)

    Tan, L.; Lin, H.; Hu, M.; Che, W.

    2014-02-01

    Shifting from macroscope models to microscope models, the agent-based approach has been widely used to model crowd evacuation as more attentions are paid on individualized behaviour. Since indoor evacuation behaviour is closely related to spatial features of the building, effective representation of indoor space is essential for the simulation of building evacuation. The traditional cell-based representation has limitations in reflecting spatial structure and is not suitable for topology analysis. Aiming at incorporating powerful topology analysis functions of GIS to facilitate agent-based simulation of building evacuation, we used a grid graph-based model in this study to represent the indoor space. Such model allows us to establish an evacuation network at a micro level. Potential escape routes from each node thus could be analysed through GIS functions of network analysis considering both the spatial structure and route capacity. This would better support agent-based modelling of evacuees' behaviour including route choice and local movements. As a case study, we conducted a simulation of emergency evacuation from the second floor of an official building using Agent Analyst as the simulation platform. The results demonstrate the feasibility of the proposed method, as well as the potential of GIS in visualizing and analysing simulation results.

  5. Integrating adaptive behaviour in large-scale flood risk assessments: an Agent-Based Modelling approach

    NASA Astrophysics Data System (ADS)

    Haer, Toon; Aerts, Jeroen

    2015-04-01

    Between 1998 and 2009, Europe suffered over 213 major damaging floods, causing 1126 deaths, displacing around half a million people. In this period, floods caused at least 52 billion euro in insured economic losses making floods the most costly natural hazard faced in Europe. In many low-lying areas, the main strategy to cope with floods is to reduce the risk of the hazard through flood defence structures, like dikes and levees. However, it is suggested that part of the responsibility for flood protection needs to shift to households and businesses in areas at risk, and that governments and insurers can effectively stimulate the implementation of individual protective measures. However, adaptive behaviour towards flood risk reduction and the interaction between the government, insurers, and individuals has hardly been studied in large-scale flood risk assessments. In this study, an European Agent-Based Model is developed including agent representatives for the administrative stakeholders of European Member states, insurers and reinsurers markets, and individuals following complex behaviour models. The Agent-Based Modelling approach allows for an in-depth analysis of the interaction between heterogeneous autonomous agents and the resulting (non-)adaptive behaviour. Existing flood damage models are part of the European Agent-Based Model to allow for a dynamic response of both the agents and the environment to changing flood risk and protective efforts. By following an Agent-Based Modelling approach this study is a first contribution to overcome the limitations of traditional large-scale flood risk models in which the influence of individual adaptive behaviour towards flood risk reduction is often lacking.

  6. Pain expressiveness and altruistic behavior: an exploration using agent-based modeling.

    PubMed

    de C Williams, Amanda C; Gallagher, Elizabeth; Fidalgo, Antonio R; Bentley, Peter J

    2016-03-01

    Predictions which invoke evolutionary mechanisms are hard to test. Agent-based modeling in artificial life offers a way to simulate behaviors and interactions in specific physical or social environments over many generations. The outcomes have implications for understanding adaptive value of behaviors in context. Pain-related behavior in animals is communicated to other animals that might protect or help, or might exploit or predate. An agent-based model simulated the effects of displaying or not displaying pain (expresser/nonexpresser strategies) when injured and of helping, ignoring, or exploiting another in pain (altruistic/nonaltruistic/selfish strategies). Agents modeled in MATLAB interacted at random while foraging (gaining energy); random injury interrupted foraging for a fixed time unless help from an altruistic agent, who paid an energy cost, speeded recovery. Environmental and social conditions also varied, and each model ran for 10,000 iterations. Findings were meaningful in that, in general, contingencies that evident from experimental work with a variety of mammals, over a few interactions, were replicated in the agent-based model after selection pressure over many generations. More energy-demanding expression of pain reduced its frequency in successive generations, and increasing injury frequency resulted in fewer expressers and altruists. Allowing exploitation of injured agents decreased expression of pain to near zero, but altruists remained. Decreasing costs or increasing benefits of helping hardly changed its frequency, whereas increasing interaction rate between injured agents and helpers diminished the benefits to both. Agent-based modeling allows simulation of complex behaviors and environmental pressures over evolutionary time.

  7. Emergence of a Snake-Like Structure in Mobile Distributed Agents: An Exploratory Agent-Based Modeling Approach

    PubMed Central

    Niazi, Muaz A.

    2014-01-01

    The body structure of snakes is composed of numerous natural components thereby making it resilient, flexible, adaptive, and dynamic. In contrast, current computer animations as well as physical implementations of snake-like autonomous structures are typically designed to use either a single or a relatively smaller number of components. As a result, not only these artificial structures are constrained by the dimensions of the constituent components but often also require relatively more computationally intensive algorithms to model and animate. Still, these animations often lack life-like resilience and adaptation. This paper presents a solution to the problem of modeling snake-like structures by proposing an agent-based, self-organizing algorithm resulting in an emergent and surprisingly resilient dynamic structure involving a minimal of interagent communication. Extensive simulation experiments demonstrate the effectiveness as well as resilience of the proposed approach. The ideas originating from the proposed algorithm can not only be used for developing self-organizing animations but can also have practical applications such as in the form of complex, autonomous, evolvable robots with self-organizing, mobile components with minimal individual computational capabilities. The work also demonstrates the utility of exploratory agent-based modeling (EABM) in the engineering of artificial life-like complex adaptive systems. PMID:24701135

  8. Emergence of a snake-like structure in mobile distributed agents: an exploratory agent-based modeling approach.

    PubMed

    Niazi, Muaz A

    2014-01-01

    The body structure of snakes is composed of numerous natural components thereby making it resilient, flexible, adaptive, and dynamic. In contrast, current computer animations as well as physical implementations of snake-like autonomous structures are typically designed to use either a single or a relatively smaller number of components. As a result, not only these artificial structures are constrained by the dimensions of the constituent components but often also require relatively more computationally intensive algorithms to model and animate. Still, these animations often lack life-like resilience and adaptation. This paper presents a solution to the problem of modeling snake-like structures by proposing an agent-based, self-organizing algorithm resulting in an emergent and surprisingly resilient dynamic structure involving a minimal of interagent communication. Extensive simulation experiments demonstrate the effectiveness as well as resilience of the proposed approach. The ideas originating from the proposed algorithm can not only be used for developing self-organizing animations but can also have practical applications such as in the form of complex, autonomous, evolvable robots with self-organizing, mobile components with minimal individual computational capabilities. The work also demonstrates the utility of exploratory agent-based modeling (EABM) in the engineering of artificial life-like complex adaptive systems.

  9. Using an agent-based model to simulate children's active travel to school.

    PubMed

    Yang, Yong; Diez-Roux, Ana V

    2013-05-26

    Despite the multiple advantages of active travel to school, only a small percentage of US children and adolescents walk or bicycle to school. Intervention studies are in a relatively early stage and evidence of their effectiveness over long periods is limited. The purpose of this study was to illustrate the utility of agent-based models in exploring how various policies may influence children's active travel to school. An agent-based model was developed to simulate children's school travel behavior within a hypothetical city. The model was used to explore the plausible implications of policies targeting two established barriers to active school travel: long distance to school and traffic safety. The percent of children who walk to school was compared for various scenarios. To maximize the percent of children who walk to school the school locations should be evenly distributed over space and children should be assigned to the closest school. In the case of interventions to improve traffic safety, targeting a smaller area around the school with greater intensity may be more effective than targeting a larger area with less intensity. Despite the challenges they present, agent based models are a useful complement to other analytical strategies in studying the plausible impact of various policies on active travel to school.

  10. Using an agent-based model to simulate children’s active travel to school

    PubMed Central

    2013-01-01

    Background Despite the multiple advantages of active travel to school, only a small percentage of US children and adolescents walk or bicycle to school. Intervention studies are in a relatively early stage and evidence of their effectiveness over long periods is limited. The purpose of this study was to illustrate the utility of agent-based models in exploring how various policies may influence children’s active travel to school. Methods An agent-based model was developed to simulate children’s school travel behavior within a hypothetical city. The model was used to explore the plausible implications of policies targeting two established barriers to active school travel: long distance to school and traffic safety. The percent of children who walk to school was compared for various scenarios. Results To maximize the percent of children who walk to school the school locations should be evenly distributed over space and children should be assigned to the closest school. In the case of interventions to improve traffic safety, targeting a smaller area around the school with greater intensity may be more effective than targeting a larger area with less intensity. Conclusions Despite the challenges they present, agent based models are a useful complement to other analytical strategies in studying the plausible impact of various policies on active travel to school. PMID:23705953

  11. Investigating mathematical models of immuno-interactions with early-stage cancer under an agent-based modelling perspective

    PubMed Central

    2013-01-01

    Many advances in research regarding immuno-interactions with cancer were developed with the help of ordinary differential equation (ODE) models. These models, however, are not effectively capable of representing problems involving individual localisation, memory and emerging properties, which are common characteristics of cells and molecules of the immune system. Agent-based modelling and simulation is an alternative paradigm to ODE models that overcomes these limitations. In this paper we investigate the potential contribution of agent-based modelling and simulation when compared to ODE modelling and simulation. We seek answers to the following questions: Is it possible to obtain an equivalent agent-based model from the ODE formulation? Do the outcomes differ? Are there any benefits of using one method compared to the other? To answer these questions, we have considered three case studies using established mathematical models of immune interactions with early-stage cancer. These case studies were re-conceptualised under an agent-based perspective and the simulation results were then compared with those from the ODE models. Our results show that it is possible to obtain equivalent agent-based models (i.e. implementing the same mechanisms); the simulation output of both types of models however might differ depending on the attributes of the system to be modelled. In some cases, additional insight from using agent-based modelling was obtained. Overall, we can confirm that agent-based modelling is a useful addition to the tool set of immunologists, as it has extra features that allow for simulations with characteristics that are closer to the biological phenomena. PMID:23734575

  12. Investigating mathematical models of immuno-interactions with early-stage cancer under an agent-based modelling perspective.

    PubMed

    Figueredo, Grazziela P; Siebers, Peer-Olaf; Aickelin, Uwe

    2013-01-01

    Many advances in research regarding immuno-interactions with cancer were developed with the help of ordinary differential equation (ODE) models. These models, however, are not effectively capable of representing problems involving individual localisation, memory and emerging properties, which are common characteristics of cells and molecules of the immune system. Agent-based modelling and simulation is an alternative paradigm to ODE models that overcomes these limitations. In this paper we investigate the potential contribution of agent-based modelling and simulation when compared to ODE modelling and simulation. We seek answers to the following questions: Is it possible to obtain an equivalent agent-based model from the ODE formulation? Do the outcomes differ? Are there any benefits of using one method compared to the other? To answer these questions, we have considered three case studies using established mathematical models of immune interactions with early-stage cancer. These case studies were re-conceptualised under an agent-based perspective and the simulation results were then compared with those from the ODE models. Our results show that it is possible to obtain equivalent agent-based models (i.e. implementing the same mechanisms); the simulation output of both types of models however might differ depending on the attributes of the system to be modelled. In some cases, additional insight from using agent-based modelling was obtained. Overall, we can confirm that agent-based modelling is a useful addition to the tool set of immunologists, as it has extra features that allow for simulations with characteristics that are closer to the biological phenomena.

  13. Financial price dynamics and agent-based models as inspired by Benoit Mandelbrot

    NASA Astrophysics Data System (ADS)

    LeBaron, Blake

    2016-12-01

    This short note draws some connections between Mandelbrot‗s empirical legacy, and the interdisciplinary work that followed in finance. Much of this work is now labeled econophysics, but some has always been more in the realm of economics than physics. In a few areas the overlap is even becoming quite complete as in market microstructure. I will also give some ideas about the various successes and failures in this area, and some directions for the future of agent- based modeling in particular.

  14. A Novel Application of Agent-based Modeling: Projecting Water Access and Availability Using a Coupled Hydrologic Agent-based Model in the Nzoia Basin, Kenya

    NASA Astrophysics Data System (ADS)

    Le, A.; Pricope, N. G.

    2015-12-01

    Projections indicate that increasing population density, food production, and urbanization in conjunction with changing climate conditions will place stress on water resource availability. As a result, a holistic understanding of current and future water resource distribution is necessary for creating strategies to identify the most sustainable means of accessing this resource. Currently, most water resource management strategies rely on the application of global climate predictions to physically based hydrologic models to understand potential changes in water availability. However, the need to focus on understanding community-level social behaviors that determine individual water usage is becoming increasingly evident, as predictions derived only from hydrologic models cannot accurately represent the coevolution of basin hydrology and human water and land usage. Models that are better equipped to represent the complexity and heterogeneity of human systems and satellite-derived products in place of or in conjunction with historic data significantly improve preexisting hydrologic model accuracy and application outcomes. We used a novel agent-based sociotechnical model that combines the Soil and Water Assessment Tool (SWAT) and Agent Analyst and applied it in the Nzoia Basin, an area in western Kenya that is becoming rapidly urbanized and industrialized. Informed by a combination of satellite-derived products and over 150 household surveys, the combined sociotechnical model provided unique insight into how populations self-organize and make decisions based on water availability. In addition, the model depicted how population organization and current management alter water availability currently and in the future.

  15. Agent-Based Phytoplankton Models of Cellular and Population Processes: Fostering Individual-Based Learning in Undergraduate Research

    NASA Astrophysics Data System (ADS)

    Berges, J. A.; Raphael, T.; Rafa Todd, C. S.; Bate, T. C.; Hellweger, F. L.

    2016-02-01

    Engaging undergraduate students in research projects that require expertise in multiple disciplines (e.g. cell biology, population ecology, and mathematical modeling) can be challenging because they have often not developed the expertise that allows them to participate at a satisfying level. Use of agent-based modeling can allow exploration of concepts at more intuitive levels, and encourage experimentation that emphasizes processes over computational skills. Over the past several years, we have involved undergraduate students in projects examining both ecological and cell biological aspects of aquatic microbial biology, using the freely-downloadable, agent-based modeling environment NetLogo (https://ccl.northwestern.edu/netlogo/). In Netlogo, actions of large numbers of individuals can be simulated, leading to complex systems with emergent behavior. The interface features appealing graphics, monitors, and control structures. In one example, a group of sophomores in a BioMathematics program developed an agent-based model of phytoplankton population dynamics in a pond ecosystem, motivated by observed macroscopic changes in cell numbers (due to growth and death), and driven by responses to irradiance, temperature and a limiting nutrient. In a second example, junior and senior undergraduates conducting Independent Studies created a model of the intracellular processes governing stress and cell death for individual phytoplankton cells (based on parameters derived from experiments using single-cell culturing and flow cytometry), and then this model was embedded in the agents in the pond ecosystem model. In our experience, students with a range of mathematical abilities learned to code quickly and could use the software with varying degrees of sophistication, for example, creation of spatially-explicit two and three-dimensional models. Skills developed quickly and transferred readily to other platforms (e.g. Matlab).

  16. Collaborative Multi-Agent Based Simulations: Stakeholder-Focused Innovation in Water Resources Management and Decision-Support Modeling

    NASA Astrophysics Data System (ADS)

    Kock, B. E.

    2006-12-01

    The combined use of multi-agent based simulations and collaborative modeling approaches is emerging as a highly effective tool for representing complex coupled social-biophysical water resource systems. A collaboratively-designed, multi-agent based simulation can be used both as a decision-support tool and as a didactic method for improving stakeholder understanding and engagement with water resources policymaking and management. Major technical and non-technical obstacles remain to the efficient and effective development of multi-agent models of human society, to integrating these models with GIS and other numerical models, and to building a process for engaging stakeholders with model design, implementation and use. It is proposed here to tackle some of these obstacles through a collaborative multi-agent based simulation process framework, intended for practical use in resolving disputes and environmental challenges over sustainable irrigated agriculture in the Western United States. A practical implementation of this framework will be conducted in collaboration with a diverse stakeholder group representing farmers and local, state and federal water managers. Through the use of simulation gaming, interviewing and computer-based knowledge elicitation, a multi-agent model representing local and regional social dynamics will be developed to support the acceptable and sustainable implementation of management alternatives for reducing regional problems of salinization and high selenium concentrations in soils and irrigation water. The development of a socially and scientifically credible simulation platform in this setting can make a significant contribution to ensuring the non-adversarial use of high quality science, enhance the engagement of stakeholders with policymaking, and help meet the challenges of integrating dynamic models of human society with more traditional biophysical systems models.

  17. Strategic directions for agent-based modeling: avoiding the YAAWN syndrome.

    PubMed

    O'Sullivan, David; Evans, Tom; Manson, Steven; Metcalf, Sara; Ligmann-Zielinska, Arika; Bone, Chris

    In this short communication, we examine how agent-based modeling has become common in land change science and is increasingly used to develop case studies for particular times and places. There is a danger that the research community is missing a prime opportunity to learn broader lessons from the use of agent-based modeling (ABM), or at the very least not sharing these lessons more widely. How do we find an appropriate balance between empirically rich, realistic models and simpler theoretically grounded models? What are appropriate and effective approaches to model evaluation in light of uncertainties not only in model parameters but also in model structure? How can we best explore hybrid model structures that enable us to better understand the dynamics of the systems under study, recognizing that no single approach is best suited to this task? Under what circumstances - in terms of model complexity, model evaluation, and model structure - can ABMs be used most effectively to lead to new insight for stakeholders? We explore these questions in the hope of helping the growing community of land change scientists using models in their research to move from 'yet another model' to doing better science with models.

  18. Integrated Agent-Based and Production Cost Modeling Framework for Renewable Energy Studies: Preprint

    SciTech Connect

    Gallo, Giulia

    2015-10-07

    The agent-based framework for renewable energy studies (ARES) is an integrated approach that adds an agent-based model of industry actors to PLEXOS and combines the strengths of the two to overcome their individual shortcomings. It can examine existing and novel wholesale electricity markets under high penetrations of renewables. ARES is demonstrated by studying how increasing levels of wind will impact the operations and the exercise of market power of generation companies that exploit an economic withholding strategy. The analysis is carried out on a test system that represents the Electric Reliability Council of Texas energy-only market in the year 2020. The results more realistically reproduce the operations of an energy market under different and increasing penetrations of wind, and ARES can be extended to address pressing issues in current and future wholesale electricity markets.

  19. Integrated Agent-Based and Production Cost Modeling Framework for Renewable Energy Studies

    SciTech Connect

    Gallo, Giulia

    2016-01-08

    The agent-based framework for renewable energy studies (ARES) is an integrated approach that adds an agent-based model of industry actors to PLEXOS and combines the strengths of the two to overcome their individual shortcomings. It can examine existing and novel wholesale electricity markets under high penetrations of renewables. ARES is demonstrated by studying how increasing levels of wind will impact the operations and the exercise of market power of generation companies that exploit an economic withholding strategy. The analysis is carried out on a test system that represents the Electric Reliability Council of Texas energy-only market in the year 2020. The results more realistically reproduce the operations of an energy market under different and increasing penetrations of wind, and ARES can be extended to address pressing issues in current and future wholesale electricity markets.

  20. Strategic directions for agent-based modeling: avoiding the YAAWN syndrome

    PubMed Central

    O’Sullivan, David; Evans, Tom; Manson, Steven; Metcalf, Sara; Ligmann-Zielinska, Arika; Bone, Chris

    2015-01-01

    In this short communication, we examine how agent-based modeling has become common in land change science and is increasingly used to develop case studies for particular times and places. There is a danger that the research community is missing a prime opportunity to learn broader lessons from the use of agent-based modeling (ABM), or at the very least not sharing these lessons more widely. How do we find an appropriate balance between empirically rich, realistic models and simpler theoretically grounded models? What are appropriate and effective approaches to model evaluation in light of uncertainties not only in model parameters but also in model structure? How can we best explore hybrid model structures that enable us to better understand the dynamics of the systems under study, recognizing that no single approach is best suited to this task? Under what circumstances – in terms of model complexity, model evaluation, and model structure – can ABMs be used most effectively to lead to new insight for stakeholders? We explore these questions in the hope of helping the growing community of land change scientists using models in their research to move from ‘yet another model’ to doing better science with models. PMID:27158257

  1. Applications of agent-based simulation for human socio-cultural behavior modeling.

    PubMed

    Jiang, Hong; Karwowski, Waldemar; Ahram, Tareq Z

    2012-01-01

    Agent-based modeling and simulation (ABMS) has gained wide attention over the past few years. ABMS is a powerful simulation modeling technique that has a number of applications, including applications to real-world business problems [1]. This modeling technique has been used by scientists to analyze complex system-level behavior by simulating the system from the bottom up. The major application of ABMS includes social, political, biology, and economic sciences. This paper provides an overview of ABMS applications with the emphasis on modeling human socio-cultural behavior (HSCB).

  2. Estimation of a simple agent-based model of financial markets: An application to Australian stock and foreign exchange data

    NASA Astrophysics Data System (ADS)

    Alfarano, Simone; Lux, Thomas; Wagner, Friedrich

    2006-10-01

    Following Alfarano et al. [Estimation of agent-based models: the case of an asymmetric herding model, Comput. Econ. 26 (2005) 19-49; Excess volatility and herding in an artificial financial market: analytical approach and estimation, in: W. Franz, H. Ramser, M. Stadler (Eds.), Funktionsfähigkeit und Stabilität von Finanzmärkten, Mohr Siebeck, Tübingen, 2005, pp. 241-254], we consider a simple agent-based model of a highly stylized financial market. The model takes Kirman's ant process [A. Kirman, Epidemics of opinion and speculative bubbles in financial markets, in: M.P. Taylor (Ed.), Money and Financial Markets, Blackwell, Cambridge, 1991, pp. 354-368; A. Kirman, Ants, rationality, and recruitment, Q. J. Econ. 108 (1993) 137-156] of mimetic contagion as its starting point, but allows for asymmetry in the attractiveness of both groups. Embedding the contagion process into a standard asset-pricing framework, and identifying the abstract groups of the herding model as chartists and fundamentalist traders, a market with periodic bubbles and bursts is obtained. Taking stock of the availability of a closed-form solution for the stationary distribution of returns for this model, we can estimate its parameters via maximum likelihood. Expanding our earlier work, this paper presents pertinent estimates for the Australian dollar/US dollar exchange rate and the Australian stock market index. As it turns out, our model indicates dominance of fundamentalist behavior in both the stock and foreign exchange market.

  3. Agent-based model of Fecal Microbial Transplant effect on Bile Acid Metabolism on suppressing Clostridium difficile infection: an example of agent-based modeling of intestinal bacterial infection

    PubMed Central

    Peer, Xavier; An, Gary

    2014-01-01

    Agent-based modeling is a computational modeling method that represents system-level behavior as arising from multiple interactions between the multiple components that make up a system. Biological systems are thus readily described using agent-based models (ABMs), as multi-cellular organisms can be viewed as populations of interacting cells, and microbial systems manifest as colonies of individual microbes. Intersections between these two domains underlie an increasing number of pathophysiological processes, and the intestinal tract represents one of the most significant locations for these inter-domain interactions, so much so that it can be considered an internal ecology of varying robustness and function. Intestinal infections represent significant disturbances of this internal ecology, and one of the most clinically relevant intestinal infections is Clostridium difficile infection (CDI). CDI is precipitated by the use of broad-spectrum antibiotics, involves the depletion of commensal microbiota, and alterations in bile acid composition in the intestinal lumen. We present an example ABM of CDI (the Clostridium difficile Infection ABM, or CDIABM) to examine fundamental dynamics of the pathogenesis of CDI and its response to treatment with anti-CDI antibiotics and a newer treatment therapy, Fecal Microbial Transplant (FMT). The CDIABM focuses on one specific mechanism of potential CDI suppression: commensal modulation of bile acid composition. Even given its abstraction, the CDIABM reproduces essential dynamics of CDI and its response to therapy, and identifies a paradoxical zone of behavior that provides insight into the role of intestinal nutritional status and the efficacy of anti-CDI therapies. It is hoped that this use case example of the CDIABM can demonstrate the usefulness of both agent-based modeling and the application of abstract functional representation as the biomedical community seeks to address the challenges of increasingly complex diseases with

  4. Agent-based model of fecal microbial transplant effect on bile acid metabolism on suppressing Clostridium difficile infection: an example of agent-based modeling of intestinal bacterial infection.

    PubMed

    Peer, Xavier; An, Gary

    2014-10-01

    Agent-based modeling is a computational modeling method that represents system-level behavior as arising from multiple interactions between the multiple components that make up a system. Biological systems are thus readily described using agent-based models (ABMs), as multi-cellular organisms can be viewed as populations of interacting cells, and microbial systems manifest as colonies of individual microbes. Intersections between these two domains underlie an increasing number of pathophysiological processes, and the intestinal tract represents one of the most significant locations for these inter-domain interactions, so much so that it can be considered an internal ecology of varying robustness and function. Intestinal infections represent significant disturbances of this internal ecology, and one of the most clinically relevant intestinal infections is Clostridium difficile infection (CDI). CDI is precipitated by the use of broad-spectrum antibiotics, involves the depletion of commensal microbiota, and alterations in bile acid composition in the intestinal lumen. We present an example ABM of CDI (the C. difficile Infection ABM, or CDIABM) to examine fundamental dynamics of the pathogenesis of CDI and its response to treatment with anti-CDI antibiotics and a newer treatment therapy, fecal microbial transplant. The CDIABM focuses on one specific mechanism of potential CDI suppression: commensal modulation of bile acid composition. Even given its abstraction, the CDIABM reproduces essential dynamics of CDI and its response to therapy, and identifies a paradoxical zone of behavior that provides insight into the role of intestinal nutritional status and the efficacy of anti-CDI therapies. It is hoped that this use case example of the CDIABM can demonstrate the usefulness of both agent-based modeling and the application of abstract functional representation as the biomedical community seeks to address the challenges of increasingly complex diseases with the goal of

  5. Agent Based Modeling of Collaboration and Work Practices Onboard the International Space Station

    NASA Technical Reports Server (NTRS)

    Acquisti, Alessandro; Sierhuis, Maarten; Clancey, William J.; Bradshaw, Jeffrey M.; Shaffo, Mike (Technical Monitor)

    2002-01-01

    The International Space Station is one the most complex projects ever, with numerous interdependent constraints affecting productivity and crew safety. This requires planning years before crew expeditions, and the use of sophisticated scheduling tools. Human work practices, however, are difficult to study and represent within traditional planning tools. We present an agent-based model and simulation of the activities and work practices of astronauts onboard the ISS based on an agent-oriented approach. The model represents 'a day in the life' of the ISS crew and is developed in Brahms, an agent-oriented, activity-based language used to model knowledge in situated action and learning in human activities.

  6. Combining Bayesian Networks and Agent Based Modeling to develop a decision-support model in Vietnam

    NASA Astrophysics Data System (ADS)

    Nong, Bao Anh; Ertsen, Maurits; Schoups, Gerrit

    2016-04-01

    Complexity and uncertainty in natural resources management have been focus themes in recent years. Within these debates, with the aim to define an approach feasible for water management practice, we are developing an integrated conceptual modeling framework for simulating decision-making processes of citizens, in our case in the Day river area, Vietnam. The model combines Bayesian Networks (BNs) and Agent-Based Modeling (ABM). BNs are able to combine both qualitative data from consultants / experts / stakeholders, and quantitative data from observations on different phenomena or outcomes from other models. Further strengths of BNs are that the relationship between variables in the system is presented in a graphical interface, and that components of uncertainty are explicitly related to their probabilistic dependencies. A disadvantage is that BNs cannot easily identify the feedback of agents in the system once changes appear. Hence, ABM was adopted to represent the reaction among stakeholders under changes. The modeling framework is developed as an attempt to gain better understanding about citizen's behavior and factors influencing their decisions in order to reduce uncertainty in the implementation of water management policy.

  7. Agent-based modeling of malaria vectors: the importance of spatial simulation

    PubMed Central

    2014-01-01

    Background The modeling of malaria vector mosquito populations yields great insight into drivers of malaria transmission at the village scale. Simulation of individual mosquitoes as “agents” in a distributed, dynamic model domain may be greatly beneficial for simulation of spatial relationships of vectors and hosts. Methods In this study, an agent-based model is used to simulate the life cycle and movement of individual malaria vector mosquitoes in a Niger Sahel village, with individual simulated mosquitoes interacting with their physical environment as well as humans. Various processes that are known to be epidemiologically important, such as the dependence of parity on flight distance between developmental habitat and blood meal hosts and therefore spatial relationships of pools and houses, are readily simulated using this modeling paradigm. Impacts of perturbations can be evaluated on the basis of vectorial capacity, because the interactions between individuals that make up the population- scale metric vectorial capacity can be easily tracked for simulated mosquitoes and human blood meal hosts, without the need to estimate vectorial capacity parameters. Results As expected, model results show pronounced impacts of pool source reduction from larvicide application and draining, but with varying degrees of impact depending on the spatial relationship between pools and human habitation. Results highlight the importance of spatially-explicit simulation that can model individuals such as in an agent-based model. Conclusions The impacts of perturbations on village scale malaria transmission depend on spatial locations of individual mosquitoes, as well as the tracking of relevant life cycle events and characteristics of individual mosquitoes. This study demonstrates advantages of using an agent-based approach for village-scale mosquito simulation to address questions in which spatial relationships are known to be important. PMID:24992942

  8. Attribute Assignment to a Synthetic Population in Support of Agent-Based Disease Modeling

    PubMed Central

    Cajka, James C.; Cooley, Philip C.; Wheaton, William D.

    2010-01-01

    Communicable-disease transmission models are useful for the testing of prevention and intervention strategies. Agent-based models (ABMs) represent a new and important class of the many types of disease transmission models in use. Agent-based disease models benefit from their ability to assign disease transmission probabilities based on characteristics shared by individual agents. These shared characteristics allow ABMs to apply transmission probabilities when agents come together in geographic space. Modeling these types of social interactions requires data, and the results of the model largely depend on the quality of these input data. We initially generated a synthetic population for the United States, in support of the Models of Infectious Disease Agent Study. Subsequently, we created shared characteristics to use in ABMs. The specific goals for this task were to assign the appropriately aged populations to schools, workplaces, and public transit. Each goal presented its own challenges and problems; therefore, we used different techniques to create each type of shared characteristic. These shared characteristics have allowed disease models to more realistically predict the spread of disease, both spatially and temporally. PMID:22577617

  9. Uses of Agent-Based Modeling for Health Communication: the TELL ME Case Study.

    PubMed

    Barbrook-Johnson, Peter; Badham, Jennifer; Gilbert, Nigel

    2016-07-19

    Government communication is an important management tool during a public health crisis, but understanding its impact is difficult. Strategies may be adjusted in reaction to developments on the ground and it is challenging to evaluate the impact of communication separately from other crisis management activities. Agent-based modeling is a well-established research tool in social science to respond to similar challenges. However, there have been few such models in public health. We use the example of the TELL ME agent-based model to consider ways in which a non-predictive policy model can assist policy makers. This model concerns individuals' protective behaviors in response to an epidemic, and the communication that influences such behavior. Drawing on findings from stakeholder workshops and the results of the model itself, we suggest such a model can be useful: (i) as a teaching tool, (ii) to test theory, and (iii) to inform data collection. We also plot a path for development of similar models that could assist with communication planning for epidemics.

  10. Attribute Assignment to a Synthetic Population in Support of Agent-Based Disease Modeling.

    PubMed

    Cajka, James C; Cooley, Philip C; Wheaton, William D

    2010-09-01

    Communicable-disease transmission models are useful for the testing of prevention and intervention strategies. Agent-based models (ABMs) represent a new and important class of the many types of disease transmission models in use. Agent-based disease models benefit from their ability to assign disease transmission probabilities based on characteristics shared by individual agents. These shared characteristics allow ABMs to apply transmission probabilities when agents come together in geographic space. Modeling these types of social interactions requires data, and the results of the model largely depend on the quality of these input data. We initially generated a synthetic population for the United States, in support of the Models of Infectious Disease Agent Study. Subsequently, we created shared characteristics to use in ABMs. The specific goals for this task were to assign the appropriately aged populations to schools, workplaces, and public transit. Each goal presented its own challenges and problems; therefore, we used different techniques to create each type of shared characteristic. These shared characteristics have allowed disease models to more realistically predict the spread of disease, both spatially and temporally.

  11. A Model of Rapid Radicalization Behavior Using Agent-Based Modeling and Quorum Sensing

    NASA Technical Reports Server (NTRS)

    Schwartz, Noah; Drucker, Nick; Campbell, Kenyth

    2012-01-01

    Understanding the dynamics of radicalization, especially rapid radicalization, has become increasingly important to US policy in the past several years. Traditionally, radicalization is considered a slow process, but recent social and political events demonstrate that the process can occur quickly. Examining this rapid process, in real time, is impossible. However, recreating an event using modeling and simulation (M&S) allows researchers to study some of the complex dynamics associated with rapid radicalization. We propose to adapt the biological mechanism of quorum sensing as a tool to explore, or possibly explain, rapid radicalization. Due to the complex nature of quorum sensing, M&S allows us to examine events that we could not otherwise examine in real time. For this study, we employ Agent Based Modeling (ABM), an M&S paradigm suited to modeling group behavior. The result of this study was the successful creation of rapid radicalization using quorum sensing. The Battle of Mogadishu was the inspiration for this model and provided the testing conditions used to explore quorum sensing and the ideas behind rapid radicalization. The final product has wider applicability however, using quorum sensing as a possible tool for examining other catalytic rapid radicalization events.

  12. Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

    NASA Astrophysics Data System (ADS)

    Alexandridis, Konstantinos T.

    This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land

  13. Genetic Algorithms for Agent-Based Infrastructure Interdependency Modeling and Analysis

    SciTech Connect

    May Permann

    2007-03-01

    Today’s society relies greatly upon an array of complex national and international infrastructure networks such as transportation, electric power, telecommunication, and financial networks. This paper describes initial research combining agent-based infrastructure modeling software and genetic algorithms (GAs) to help optimize infrastructure protection and restoration decisions. This research proposes to apply GAs to the problem of infrastructure modeling and analysis in order to determine the optimum assets to restore or protect from attack or other disaster. This research is just commencing and therefore the focus of this paper is the integration of a GA optimization method with a simulation through the simulation’s agents.

  14. Is the person-situation debate important for agent-based modeling and vice-versa?

    PubMed

    Sznajd-Weron, Katarzyna; Szwabiński, Janusz; Weron, Rafał

    2014-01-01

    Agent-based models (ABM) are believed to be a very powerful tool in the social sciences, sometimes even treated as a substitute for social experiments. When building an ABM we have to define the agents and the rules governing the artificial society. Given the complexity and our limited understanding of the human nature, we face the problem of assuming that either personal traits, the situation or both have impact on the social behavior of agents. However, as the long-standing person-situation debate in psychology shows, there is no consensus as to the underlying psychological mechanism and the important question that arises is whether the modeling assumptions we make will have a substantial influence on the simulated behavior of the system as a whole or not. Studying two variants of the same agent-based model of opinion formation, we show that the decision to choose either personal traits or the situation as the primary factor driving social interactions is of critical importance. Using Monte Carlo simulations (for Barabasi-Albert networks) and analytic calculations (for a complete graph) we provide evidence that assuming a person-specific response to social influence at the microscopic level generally leads to a completely different and less realistic aggregate or macroscopic behavior than an assumption of a situation-specific response; a result that has been reported by social psychologists for a range of experimental setups, but has been downplayed or ignored in the opinion dynamics literature. This sensitivity to modeling assumptions has far reaching consequences also beyond opinion dynamics, since agent-based models are becoming a popular tool among economists and policy makers and are often used as substitutes of real social experiments.

  15. Is the Person-Situation Debate Important for Agent-Based Modeling and Vice-Versa?

    PubMed Central

    Sznajd-Weron, Katarzyna; Szwabiński, Janusz; Weron, Rafał

    2014-01-01

    Background Agent-based models (ABM) are believed to be a very powerful tool in the social sciences, sometimes even treated as a substitute for social experiments. When building an ABM we have to define the agents and the rules governing the artificial society. Given the complexity and our limited understanding of the human nature, we face the problem of assuming that either personal traits, the situation or both have impact on the social behavior of agents. However, as the long-standing person-situation debate in psychology shows, there is no consensus as to the underlying psychological mechanism and the important question that arises is whether the modeling assumptions we make will have a substantial influence on the simulated behavior of the system as a whole or not. Methodology/Principal Findings Studying two variants of the same agent-based model of opinion formation, we show that the decision to choose either personal traits or the situation as the primary factor driving social interactions is of critical importance. Using Monte Carlo simulations (for Barabasi-Albert networks) and analytic calculations (for a complete graph) we provide evidence that assuming a person-specific response to social influence at the microscopic level generally leads to a completely different and less realistic aggregate or macroscopic behavior than an assumption of a situation-specific response; a result that has been reported by social psychologists for a range of experimental setups, but has been downplayed or ignored in the opinion dynamics literature. Significance This sensitivity to modeling assumptions has far reaching consequences also beyond opinion dynamics, since agent-based models are becoming a popular tool among economists and policy makers and are often used as substitutes of real social experiments. PMID:25369531

  16. Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

    PubMed Central

    Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.

    2015-01-01

    Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

  17. A spatial web/agent-based model to support stakeholders' negotiation regarding land development.

    PubMed

    Pooyandeh, Majeed; Marceau, Danielle J

    2013-11-15

    Decision making in land management can be greatly enhanced if the perspectives of concerned stakeholders are taken into consideration. This often implies negotiation in order to reach an agreement based on the examination of multiple alternatives. This paper describes a spatial web/agent-based modeling system that was developed to support the negotiation process of stakeholders regarding land development in southern Alberta, Canada. This system integrates a fuzzy analytic hierarchy procedure within an agent-based model in an interactive visualization environment provided through a web interface to facilitate the learning and negotiation of the stakeholders. In the pre-negotiation phase, the stakeholders compare their evaluation criteria using linguistic expressions. Due to the uncertainty and fuzzy nature of such comparisons, a fuzzy Analytic Hierarchy Process is then used to prioritize the criteria. The negotiation starts by a development plan being submitted by a user (stakeholder) through the web interface. An agent called the proposer, which represents the proposer of the plan, receives this plan and starts negotiating with all other agents. The negotiation is conducted in a step-wise manner where the agents change their attitudes by assigning a new set of weights to their criteria. If an agreement is not achieved, a new location for development is proposed by the proposer agent. This process is repeated until a location is found that satisfies all agents to a certain predefined degree. To evaluate the performance of the model, the negotiation was simulated with four agents, one of which being the proposer agent, using two hypothetical development plans. The first plan was selected randomly; the other one was chosen in an area that is of high importance to one of the agents. While the agents managed to achieve an agreement about the location of the land development after three rounds of negotiation in the first scenario, seven rounds were required in the second

  18. An Agent-Based Model of Farmer Decision Making in Jordan

    NASA Astrophysics Data System (ADS)

    Selby, Philip; Medellin-Azuara, Josue; Harou, Julien; Klassert, Christian; Yoon, Jim

    2016-04-01

    We describe an agent based hydro-economic model of groundwater irrigated agriculture in the Jordan Highlands. The model employs a Multi-Agent-Simulation (MAS) framework and is designed to evaluate direct and indirect outcomes of climate change scenarios and policy interventions on farmer decision making, including annual land use, groundwater use for irrigation, and water sales to a water tanker market. Land use and water use decisions are simulated for groups of farms grouped by location and their behavioural and economic similarities. Decreasing groundwater levels, and the associated increase in pumping costs, are important drivers for change within Jordan'S agricultural sector. We describe how this is considered by coupling of agricultural and groundwater models. The agricultural production model employs Positive Mathematical Programming (PMP), a method for calibrating agricultural production functions to observed planted areas. PMP has successfully been used with disaggregate models for policy analysis. We adapt the PMP approach to allow explicit evaluation of the impact of pumping costs, groundwater purchase fees and a water tanker market. The work demonstrates the applicability of agent-based agricultural decision making assessment in the Jordan Highlands and its integration with agricultural model calibration methods. The proposed approach is designed and implemented with software such that it could be used to evaluate a variety of physical and human influences on decision making in agricultural water management.

  19. Agent-based modeling of deforestation in southern Yucatán, Mexico, and reforestation in the Midwest United States

    PubMed Central

    Manson, Steven M.; Evans, Tom

    2007-01-01

    We combine mixed-methods research with integrated agent-based modeling to understand land change and economic decision making in the United States and Mexico. This work demonstrates how sustainability science benefits from combining integrated agent-based modeling (which blends methods from the social, ecological, and information sciences) and mixed-methods research (which interleaves multiple approaches ranging from qualitative field research to quantitative laboratory experiments and interpretation of remotely sensed imagery). We test assumptions of utility-maximizing behavior in household-level landscape management in south-central Indiana, linking parcel data, land cover derived from aerial photography, and findings from laboratory experiments. We examine the role of uncertainty and limited information, preferences, differential demographic attributes, and past experience and future time horizons. We also use evolutionary programming to represent bounded rationality in agriculturalist households in the southern Yucatán of Mexico. This approach captures realistic rule of thumb strategies while identifying social and environmental factors in a manner similar to econometric models. These case studies highlight the role of computational models of decision making in land-change contexts and advance our understanding of decision making in general. PMID:18093928

  20. Agent-based modeling of deforestation in southern Yucatan, Mexico, and reforestation in the Midwest United States.

    PubMed

    Manson, Steven M; Evans, Tom

    2007-12-26

    We combine mixed-methods research with integrated agent-based modeling to understand land change and economic decision making in the United States and Mexico. This work demonstrates how sustainability science benefits from combining integrated agent-based modeling (which blends methods from the social, ecological, and information sciences) and mixed-methods research (which interleaves multiple approaches ranging from qualitative field research to quantitative laboratory experiments and interpretation of remotely sensed imagery). We test assumptions of utility-maximizing behavior in household-level landscape management in south-central Indiana, linking parcel data, land cover derived from aerial photography, and findings from laboratory experiments. We examine the role of uncertainty and limited information, preferences, differential demographic attributes, and past experience and future time horizons. We also use evolutionary programming to represent bounded rationality in agriculturalist households in the southern Yucatán of Mexico. This approach captures realistic rule of thumb strategies while identifying social and environmental factors in a manner similar to econometric models. These case studies highlight the role of computational models of decision making in land-change contexts and advance our understanding of decision making in general.

  1. Simulating the elimination of sleeping sickness with an agent-based model

    PubMed Central

    Grébaut, Pascal; Girardin, Killian; Fédérico, Valentine; Bousquet, François

    2016-01-01

    Although Human African Trypanosomiasis is largely considered to be in the process of extinction today, the persistence of human and animal reservoirs, as well as the vector, necessitates a laborious elimination process. In this context, modeling could be an effective tool to evaluate the ability of different public health interventions to control the disease. Using the Cormas® system, we developed HATSim, an agent-based model capable of simulating the possible endemic evolutions of sleeping sickness and the ability of National Control Programs to eliminate the disease. This model takes into account the analysis of epidemiological, entomological, and ecological data from field studies conducted during the last decade, making it possible to predict the evolution of the disease within this area over a 5-year span. In this article, we first present HATSim according to the Overview, Design concepts, and Details (ODD) protocol that is classically used to describe agent-based models, then, in a second part, we present predictive results concerning the evolution of Human African Trypanosomiasis in the village of Lambi (Cameroon), in order to illustrate the interest of such a tool. Our results are consistent with what was observed in the field by the Cameroonian National Control Program (CNCP). Our simulations also revealed that regular screening can be sufficient, although vector control applied to all areas with human activities could be significantly more efficient. Our results indicate that the current model can already help decision-makers in planning the elimination of the disease in foci. PMID:28008825

  2. Agent-based Model for the Coupled Human-Climate System

    NASA Astrophysics Data System (ADS)

    Zvoleff, A.; Werner, B.

    2006-12-01

    Integrated assessment models have been used to predict the outcome of coupled economic growth, resource use, greenhouse gas emissions and climate change, both for scientific and policy purposes. These models generally have employed significant simplifications that suppress nonlinearities and the possibility of multiple equilibria in both their economic (DeCanio, 2005) and climate (Schneider and Kuntz-Duriseti, 2002) components. As one step toward exploring general features of the nonlinear dynamics of the coupled system, we have developed a series of variations on the well studied RICE and DICE models, which employ different forms of agent-based market dynamics and "climate surprises." Markets are introduced through the replacement of the production function of the DICE/RICE models with an agent-based market modeling the interactions of producers, policymakers, and consumer agents. Technological change and population growth are treated endogenously. Climate surprises are representations of positive (for example, ice sheet collapse) or negative (for example, increased aerosols from desertification) feedbacks that are turned on with probability depending on warming. Initial results point toward the possibility of large amplitude instabilities in the coupled human-climate system owing to the mismatch between short outlook market dynamics and long term climate responses. Implications for predictability of future climate will be discussed. Supported by the Andrew W Mellon Foundation and the UC Academic Senate.

  3. An Agent-Based Model of Centralized Institutions, Social Network Technology, and Revolution

    PubMed Central

    Makowsky, Michael D.; Rubin, Jared

    2013-01-01

    This paper sheds light on the general mechanisms underlying large-scale social and institutional change. We employ an agent-based model to test the impact of authority centralization and social network technology on preference falsification and institutional change. We find that preference falsification is increasing with centralization and decreasing with social network range. This leads to greater cascades of preference revelation and thus more institutional change in highly centralized societies and this effect is exacerbated at greater social network ranges. An empirical analysis confirms the connections that we find between institutional centralization, social radius, preference falsification, and institutional change. PMID:24278280

  4. Advancing complementary and alternative medicine through social network analysis and agent-based modeling.

    PubMed

    Frantz, Terrill L

    2012-01-01

    This paper introduces the contemporary perspectives and techniques of social network analysis (SNA) and agent-based modeling (ABM) and advocates applying them to advance various aspects of complementary and alternative medicine (CAM). SNA and ABM are invaluable methods for representing, analyzing and projecting complex, relational, social phenomena; they provide both an insightful vantage point and a set of analytic tools that can be useful in a wide range of contexts. Applying these methods in the CAM context can aid the ongoing advances in the CAM field, in both its scientific aspects and in developing broader acceptance in associated stakeholder communities.

  5. Accounting for intrapopulation variability in biogeochemical models using agent-based methods.

    PubMed

    Hellweger, Ferdi L; Kianirad, Ehsan

    2007-04-15

    Present biogeochemical models typically use a lumped-system (population-level) modeling (LSM) approach that assumes average properties of a population within a control volume. For modern models that formulate phytoplankton growth as a nonlinear function of the internal nutrient (e.g., Droop kinetics), this averaging assumption can introduce a significant error. Agent-based (individual-based) modeling (ABM) is an alternative approach that does not make the assumption of average properties. This paper presents a new agent-based phytoplankton model called iAlgae. The model is contrasted to a conventional lumped-system model, constructed based on identical underlying sub-models of nutrient uptake (including luxury uptake) and growth (cell quota, Droop model). The two models are validated against laboratory data and applied to a realistic scenario, consisting of a point source nutrient discharge into a river. For the realistic scenario, the ABM-predicted phytoplankton bloom is significantly lower than the LSM-predicted one, which is due to the intrapopulation distribution in cell quotas (due to different life histories of individuals) and nonlinearity of the growth rate model. In the ABM, a fraction of the population accumulates nutrients in excess of their immediate growth requirement (luxury uptake), leaving less for the remainder. Because the model is nonlinear, this results in a suboptimal (from a population perspective) utilization of nutrient and a lower population-level growth rate, compared to the case of no intrapopulation variability assumed by the LSM model. In general, the ABM and LSM approaches can produce significantly different results when incompletely mixed conditions lead to intrapopulation variability in cell properties (i.e., cell quota) and the model equations are nonlinear.

  6. Social network analysis and agent-based modeling in social epidemiology

    PubMed Central

    2012-01-01

    The past five years have seen a growth in the interest in systems approaches in epidemiologic research. These approaches may be particularly appropriate for social epidemiology. Social network analysis and agent-based models (ABMs) are two approaches that have been used in the epidemiologic literature. Social network analysis involves the characterization of social networks to yield inference about how network structures may influence risk exposures among those in the network. ABMs can promote population-level inference from explicitly programmed, micro-level rules in simulated populations over time and space. In this paper, we discuss the implementation of these models in social epidemiologic research, highlighting the strengths and weaknesses of each approach. Network analysis may be ideal for understanding social contagion, as well as the influences of social interaction on population health. However, network analysis requires network data, which may sacrifice generalizability, and causal inference from current network analytic methods is limited. ABMs are uniquely suited for the assessment of health determinants at multiple levels of influence that may couple with social interaction to produce population health. ABMs allow for the exploration of feedback and reciprocity between exposures and outcomes in the etiology of complex diseases. They may also provide the opportunity for counterfactual simulation. However, appropriate implementation of ABMs requires a balance between mechanistic rigor and model parsimony, and the precision of output from complex models is limited. Social network and agent-based approaches are promising in social epidemiology, but continued development of each approach is needed. PMID:22296660

  7. Modeling the Population Dynamics of Antibiotic-Resistant Bacteria:. AN Agent-Based Approach

    NASA Astrophysics Data System (ADS)

    Murphy, James T.; Walshe, Ray; Devocelle, Marc

    The response of bacterial populations to antibiotic treatment is often a function of a diverse range of interacting factors. In order to develop strategies to minimize the spread of antibiotic resistance in pathogenic bacteria, a sound theoretical understanding of the systems of interactions taking place within a colony must be developed. The agent-based approach to modeling bacterial populations is a useful tool for relating data obtained at the molecular and cellular level with the overall population dynamics. Here we demonstrate an agent-based model, called Micro-Gen, which has been developed to simulate the growth and development of bacterial colonies in culture. The model also incorporates biochemical rules and parameters describing the kinetic interactions of bacterial cells with antibiotic molecules. Simulations were carried out to replicate the development of methicillin-resistant S. aureus (MRSA) colonies growing in the presence of antibiotics. The model was explored to see how the properties of the system emerge from the interactions of the individual bacterial agents in order to achieve a better mechanistic understanding of the population dynamics taking place. Micro-Gen provides a good theoretical framework for investigating the effects of local environmental conditions and cellular properties on the response of bacterial populations to antibiotic exposure in the context of a simulated environment.

  8. Nonlinear scaling analysis approach of agent-based Potts financial dynamical model.

    PubMed

    Hong, Weijia; Wang, Jun

    2014-12-01

    A financial agent-based price model is developed and investigated by one of statistical physics dynamic systems-the Potts model. Potts model, a generalization of the Ising model to more than two components, is a model of interacting spins on a crystalline lattice which describes the interaction strength among the agents. In this work, we investigate and analyze the correlation behavior of normalized returns of the proposed financial model by the power law classification scheme analysis and the empirical mode decomposition analysis. Moreover, the daily returns of Shanghai Composite Index and Shenzhen Component Index are considered, and the comparison nonlinear analysis of statistical behaviors of returns between the actual data and the simulation data is exhibited.

  9. Preliminary analysis of an agent-based model for a tick-borne disease.

    PubMed

    Gaff, Holly

    2011-04-01

    Ticks have a unique life history including a distinct set of life stages and a single blood meal per life stage. This makes tick-host interactions more complex from a mathematical perspective. In addition, any model of these interactions must involve a significant degree of stochasticity on the individual tick level. In an attempt to quantify these relationships, I have developed an individual-based model of the interactions between ticks and their hosts as well as the transmission of tick-borne disease between the two populations. The results from this model are compared with those from previously published differential equation based population models. The findings show that the agent-based model produces significantly lower prevalence of disease in both the ticks and their hosts than what is predicted by a similar differential equation model.

  10. Designing across ages: Multi-agent-based models and learning electricity

    NASA Astrophysics Data System (ADS)

    Sengupta, Pratim

    Electricity is regarded as one of the most challenging topics for students at all levels -- middle school -- college (Cohen, Eylon, & Ganiel, 1983; Belcher & Olbert, 2003; Eylon & Ganiel, 1990; Steinberg et al., 1985). Several researchers have suggested that naive misconceptions about electricity stem from a deep incommensurability (Slotta & Chi, 2006; Chi, 2005) or incompatibility (Chi, Slotta & Leauw, 1994; Reiner, Slotta, Chi, & Resnick, 2000) between naive and expert knowledge structures. I first present an alternative theoretical framework that adopts an emergent levels-based perspective as proposed by Wilensky & Resnick (1999). From this perspective, macro-level phenomena such as electric current and resistance, as well as behavior of linear electric circuits, can be conceived of as emergent from simple, body-syntonic interactions between electrons and ions in a circuit. I argue that adopting such a perspective enables us to reconceive commonly noted misconceptions in electricity as behavioral evidences of "slippage between levels" -- i.e., these misconceptions appear when otherwise productive knowledge elements are sometimes inappropriately activated due to certain macro-level phenomenological cues only -- and, that the same knowledge elements when activated due to phenomenological cues at both micro- and macro-levels, can engender a deeper, expert-like understanding. I will then introduce NIELS (NetLogo Investigations In Electromagnetism, Sengupta & Wilensky, 2006, 2008, 2009), a low-threshold high-ceiling (LTHC) learning environment of multi-agent-based computational models that represent phenomena such as electric current and resistance, as well as the behavior of linear electric circuits, as emergent. I also present results from implementations of NIELS in 5th, 7th and 12th grade classrooms that show the following: (a) how leveraging certain "design elements" over others in NIELS models can create new phenomenological cues, which in turn can be

  11. Agent-Based Modeling of the Immune System: NetLogo, a Promising Framework

    PubMed Central

    Chiacchio, Ferdinando; Russo, Giulia; Pappalardo, Francesco

    2014-01-01

    Several components that interact with each other to evolve a complex, and, in some cases, unexpected behavior, represents one of the main and fascinating features of the mammalian immune system. Agent-based modeling and cellular automata belong to a class of discrete mathematical approaches in which entities (agents) sense local information and undertake actions over time according to predefined rules. The strength of this approach is characterized by the appearance of a global behavior that emerges from interactions among agents. This behavior is unpredictable, as it does not follow linear rules. There are a lot of works that investigates the immune system with agent-based modeling and cellular automata. They have shown the ability to see clearly and intuitively into the nature of immunological processes. NetLogo is a multiagent programming language and modeling environment for simulating complex phenomena. It is designed for both research and education and is used across a wide range of disciplines and education levels. In this paper, we summarize NetLogo applications to immunology and, particularly, how this framework can help in the development and formulation of hypotheses that might drive further experimental investigations of disease mechanisms. PMID:24864263

  12. Agent-based modeling of the immune system: NetLogo, a promising framework.

    PubMed

    Chiacchio, Ferdinando; Pennisi, Marzio; Russo, Giulia; Motta, Santo; Pappalardo, Francesco

    2014-01-01

    Several components that interact with each other to evolve a complex, and, in some cases, unexpected behavior, represents one of the main and fascinating features of the mammalian immune system. Agent-based modeling and cellular automata belong to a class of discrete mathematical approaches in which entities (agents) sense local information and undertake actions over time according to predefined rules. The strength of this approach is characterized by the appearance of a global behavior that emerges from interactions among agents. This behavior is unpredictable, as it does not follow linear rules. There are a lot of works that investigates the immune system with agent-based modeling and cellular automata. They have shown the ability to see clearly and intuitively into the nature of immunological processes. NetLogo is a multiagent programming language and modeling environment for simulating complex phenomena. It is designed for both research and education and is used across a wide range of disciplines and education levels. In this paper, we summarize NetLogo applications to immunology and, particularly, how this framework can help in the development and formulation of hypotheses that might drive further experimental investigations of disease mechanisms.

  13. Combining agent-based modeling and life cycle assessment for the evaluation of mobility policies.

    PubMed

    Florent, Querini; Enrico, Benetto

    2015-02-03

    This article presents agent-based modeling (ABM) as a novel approach for consequential life cycle assessment (C-LCA) of large scale policies, more specifically mobility-related policies. The approach is validated at the Luxembourgish level (as a first case study). The agent-based model simulates the car market (sales, use, and dismantling) of the population of users in the period 2013-2020, following the implementation of different mobility policies and available electric vehicles. The resulting changes in the car fleet composition as well as the hourly uses of the vehicles are then used to derive consistent LCA results, representing the consequences of the policies. Policies will have significant environmental consequences: when using ReCiPe2008, we observe a decrease of global warming, fossil depletion, acidification, ozone depletion, and photochemical ozone formation and an increase of metal depletion, ionizing radiations, marine eutrophication, and particulate matter formation. The study clearly shows that the extrapolation of LCA results for the circulating fleet at national scale following the introduction of the policies from the LCAs of single vehicles by simple up-scaling (using hypothetical deployment scenarios) would be flawed. The inventory has to be directly conducted at full scale and to this aim, ABM is indeed a promising approach, as it allows identifying and quantifying emerging effects while modeling the Life Cycle Inventory of vehicles at microscale through the concept of agents.

  14. Agent-based re-engineering of ErbB signaling: a modeling pipeline for integrative systems biology.

    PubMed

    Das, Arya A; Ajayakumar Darsana, T; Jacob, Elizabeth

    2017-03-01

    Experiments in systems biology are generally supported by a computational model which quantitatively estimates the parameters of the system by finding the best fit to the experiment. Mathematical models have proved to be successful in reverse engineering the system. The data generated is interpreted to understand the dynamics of the underlying phenomena. The question we have sought to answer is that - is it possible to use an agent-based approach to re-engineer a biological process, making use of the available knowledge from experimental and modelling efforts? Can the bottom-up approach benefit from the top-down exercise so as to create an integrated modelling formalism for systems biology? We propose a modelling pipeline that learns from the data given by reverse engineering, and uses it for re-engineering the system, to carry out in-silico experiments. A mathematical model that quantitatively predicts co-expression of EGFR-HER2 receptors in activation and trafficking has been taken for this study. The pipeline architecture takes cues from the population model that gives the rates of biochemical reactions, to formulate knowledge-based rules for the particle model. Agent-based simulations using these rules, support the existing facts on EGFR-HER2 dynamics. We conclude that, re-engineering models, built using the results of reverse engineering, opens up the possibility of harnessing the power pack of data which now lies scattered in literature. Virtual experiments could then become more realistic when empowered with the findings of empirical cell biology and modelling studies. Implemented on the Agent Modelling Framework developed in-house. C ++ code templates available in Supplementary material . liz.csir@gmail.com. Supplementary data are available at Bioinformatics online.

  15. iCrowd: agent-based behavior modeling and crowd simulator

    NASA Astrophysics Data System (ADS)

    Kountouriotis, Vassilios I.; Paterakis, Manolis; Thomopoulos, Stelios C. A.

    2016-05-01

    Initially designed in the context of the TASS (Total Airport Security System) FP-7 project, the Crowd Simulation platform developed by the Integrated Systems Lab of the Institute of Informatics and Telecommunications at N.C.S.R. Demokritos, has evolved into a complete domain-independent agent-based behavior simulator with an emphasis on crowd behavior and building evacuation simulation. Under continuous development, it reflects an effort to implement a modern, multithreaded, data-oriented simulation engine employing latest state-of-the-art programming technologies and paradigms. It is based on an extensible architecture that separates core services from the individual layers of agent behavior, offering a concrete simulation kernel designed for high-performance and stability. Its primary goal is to deliver an abstract platform to facilitate implementation of several Agent-Based Simulation solutions with applicability in several domains of knowledge, such as: (i) Crowd behavior simulation during [in/out] door evacuation. (ii) Non-Player Character AI for Game-oriented applications and Gamification activities. (iii) Vessel traffic modeling and simulation for Maritime Security and Surveillance applications. (iv) Urban and Highway Traffic and Transportation Simulations. (v) Social Behavior Simulation and Modeling.

  16. Group-Wise Herding Behavior in Financial Markets: An Agent-Based Modeling Approach

    PubMed Central

    Kim, Minsung; Kim, Minki

    2014-01-01

    In this paper, we shed light on the dynamic characteristics of rational group behaviors and the relationship between monetary policy and economic units in the financial market by using an agent-based model (ABM), the Hurst exponent, and the Shannon entropy. First, an agent-based model is used to analyze the characteristics of the group behaviors at different levels of irrationality. Second, the Hurst exponent is applied to analyze the characteristics of the trend-following irrationality group. Third, the Shannon entropy is used to analyze the randomness and unpredictability of group behavior. We show that in a system that focuses on macro-monetary policy, steep fluctuations occur, meaning that the medium-level irrationality group has the highest Hurst exponent and Shannon entropy among all of the groups. However, in a system that focuses on micro-monetary policy, all group behaviors follow a stable trend, and the medium irrationality group thus remains stable, too. Likewise, in a system that focuses on both micro- and macro-monetary policies, all groups tend to be stable. Consequently, we find that group behavior varies across economic units at each irrationality level for micro- and macro-monetary policy in the financial market. Together, these findings offer key insights into monetary policy. PMID:24714635

  17. Agent-based modeling of osteogenic differentiation of mesenchymal stem cells in porous biomaterials.

    PubMed

    Bayrak, Elif S; Mehdizadeh, Hamidreza; Akar, Banu; Somo, Sami I; Brey, Eric M; Cinar, Ali

    2014-01-01

    Mesenchymal stem cells (MSC) have shown promise in tissue engineering applications due to their potential for differentiating into mesenchymal tissues such as osteocytes, chondrocytes, and adipocytes and releasing proteins to promote tissue regeneration. One application involves seeding MSCs in biomaterial scaffolds to promote osteogenesis in the repair of bone defects following implantation. However, predicting in vivo survival and differentiation of MSCs in biomaterials is challenging. Rapid and stable vascularization of scaffolds is required to supply nutrients and oxygen that MSCs need to survive as well as to go through osteogenic differentiation. The objective of this study is to develop an agent-based model and simulator that can be used to investigate the effects of using gradient growth factors on survival and differentiation of MSCs seeded in scaffolds. An agent-based model is developed to simulate the MSC behavior. The effect of vascular endothelial growth factor (VEGF) and bone morphogenic protein-2 (BMP-2) on both survival and osteogenic differentiation is studied. Results showed that the survival ratio of MSCs can be enhanced by increasing VEGF concentration. BMP-2 caused a slight increase on survival ratio. Osteogenesis strongly depends on the VEGF concentration as well because of its effect on vascularization. BMP-2 increased the osteogenic differentiation of MSCs.

  18. Group-wise herding behavior in financial markets: an agent-based modeling approach.

    PubMed

    Kim, Minsung; Kim, Minki

    2014-01-01

    In this paper, we shed light on the dynamic characteristics of rational group behaviors and the relationship between monetary policy and economic units in the financial market by using an agent-based model (ABM), the Hurst exponent, and the Shannon entropy. First, an agent-based model is used to analyze the characteristics of the group behaviors at different levels of irrationality. Second, the Hurst exponent is applied to analyze the characteristics of the trend-following irrationality group. Third, the Shannon entropy is used to analyze the randomness and unpredictability of group behavior. We show that in a system that focuses on macro-monetary policy, steep fluctuations occur, meaning that the medium-level irrationality group has the highest Hurst exponent and Shannon entropy among all of the groups. However, in a system that focuses on micro-monetary policy, all group behaviors follow a stable trend, and the medium irrationality group thus remains stable, too. Likewise, in a system that focuses on both micro- and macro-monetary policies, all groups tend to be stable. Consequently, we find that group behavior varies across economic units at each irrationality level for micro- and macro-monetary policy in the financial market. Together, these findings offer key insights into monetary policy.

  19. Estimating Impacts of Climate Change Policy on Land Use: An Agent-Based Modelling Approach

    PubMed Central

    2015-01-01

    Agriculture is important to New Zealand’s economy. Like other primary producers, New Zealand strives to increase agricultural output while maintaining environmental integrity. Utilising modelling to explore the economic, environmental and land use impacts of policy is critical to understand the likely effects on the sector. Key deficiencies within existing land use and land cover change models are the lack of heterogeneity in farmers and their behaviour, the role that social networks play in information transfer, and the abstraction of the global and regional economic aspects within local-scale approaches. To resolve these issues we developed the Agent-based Rural Land Use New Zealand model. The model utilises a partial equilibrium economic model and an agent-based decision-making framework to explore how the cumulative effects of individual farmer’s decisions affect farm conversion and the resulting land use at a catchment scale. The model is intended to assist in the development of policy to shape agricultural land use intensification in New Zealand. We illustrate the model, by modelling the impact of a greenhouse gas price on farm-level land use, net revenue, and environmental indicators such as nutrient losses and soil erosion for key enterprises in the Hurunui and Waiau catchments of North Canterbury in New Zealand. Key results from the model show that farm net revenue is estimated to increase over time regardless of the greenhouse gas price. Net greenhouse gas emissions are estimated to decline over time, even under a no GHG price baseline, due to an expansion of forestry on low productivity land. Higher GHG prices provide a greater net reduction of emissions. While social and geographic network effects have minimal impact on net revenue and environmental outputs for the catchment, they do have an effect on the spatial arrangement of land use and in particular the clustering of enterprises. PMID:25996591

  20. Estimating impacts of climate change policy on land use: an agent-based modelling approach.

    PubMed

    Morgan, Fraser J; Daigneault, Adam J

    2015-01-01

    Agriculture is important to New Zealand's economy. Like other primary producers, New Zealand strives to increase agricultural output while maintaining environmental integrity. Utilising modelling to explore the economic, environmental and land use impacts of policy is critical to understand the likely effects on the sector. Key deficiencies within existing land use and land cover change models are the lack of heterogeneity in farmers and their behaviour, the role that social networks play in information transfer, and the abstraction of the global and regional economic aspects within local-scale approaches. To resolve these issues we developed the Agent-based Rural Land Use New Zealand model. The model utilises a partial equilibrium economic model and an agent-based decision-making framework to explore how the cumulative effects of individual farmer's decisions affect farm conversion and the resulting land use at a catchment scale. The model is intended to assist in the development of policy to shape agricultural land use intensification in New Zealand. We illustrate the model, by modelling the impact of a greenhouse gas price on farm-level land use, net revenue, and environmental indicators such as nutrient losses and soil erosion for key enterprises in the Hurunui and Waiau catchments of North Canterbury in New Zealand. Key results from the model show that farm net revenue is estimated to increase over time regardless of the greenhouse gas price. Net greenhouse gas emissions are estimated to decline over time, even under a no GHG price baseline, due to an expansion of forestry on low productivity land. Higher GHG prices provide a greater net reduction of emissions. While social and geographic network effects have minimal impact on net revenue and environmental outputs for the catchment, they do have an effect on the spatial arrangement of land use and in particular the clustering of enterprises.

  1. Linking MODFLOW with an agent-based land-use model to support decision making.

    PubMed

    Reeves, Howard W; Zellner, Moira L

    2010-01-01

    The U.S. Geological Survey numerical groundwater flow model, MODFLOW, was integrated with an agent-based land-use model to yield a simulator for environmental planning studies. Ultimately, this integrated simulator will be used as a means to organize information, illustrate potential system responses, and facilitate communication within a participatory modeling framework. Initial results show the potential system response to different zoning policy scenarios in terms of the spatial patterns of development, which is referred to as urban form, and consequent impacts on groundwater levels. These results illustrate how the integrated simulator is capable of representing the complexity of the system. From a groundwater modeling perspective, the most important aspect of the integration is that the simulator generates stresses on the groundwater system within the simulation in contrast to the traditional approach that requires the user to specify the stresses through time.

  2. Linking MODFLOW with an agent-based land-use model to support decision making

    USGS Publications Warehouse

    Reeves, H.W.; Zellner, M.L.

    2010-01-01

    The U.S. Geological Survey numerical groundwater flow model, MODFLOW, was integrated with an agent-based land-use model to yield a simulator for environmental planning studies. Ultimately, this integrated simulator will be used as a means to organize information, illustrate potential system responses, and facilitate communication within a participatory modeling framework. Initial results show the potential system response to different zoning policy scenarios in terms of the spatial patterns of development, which is referred to as urban form, and consequent impacts on groundwater levels. These results illustrate how the integrated simulator is capable of representing the complexity of the system. From a groundwater modeling perspective, the most important aspect of the integration is that the simulator generates stresses on the groundwater system within the simulation in contrast to the traditional approach that requires the user to specify the stresses through time. Copyright ?? 2010 The Author(s). Journal compilation ?? 2010 National Ground Water Association.

  3. Health care supply networks in tightly and loosely coupled structures: exploration using agent-based modelling

    NASA Astrophysics Data System (ADS)

    Kanagarajah, A.; Parker, D.; Xu, H.

    2010-03-01

    Health care supply networks are multi-faceted complex structures. This article discusses architecture of complex systems and an agent-based modelling framework to study health care supply networks and their impact on patient safety, economics, and workloads. Here we demonstrate the application of a safety dynamics model proposed by Cook and Rasmussen (2005, '"Going Solid": A Model of System Dynamics and Consequences for Patient Safety', Quality & Safety in Health Care, 14, 67-84.) to study a health care system, using a hypothetical simulation of an emergency department as a representative unit and its dynamic behaviour. By means of simulation, this article demonstrates the non-linear behaviours of a health service unit and its complexities; and how the safety dynamic model may be used to evaluate the various policy and design aspects of health care supply networks.

  4. Decision-Making in Agent-Based Models of Migration: State of the Art and Challenges.

    PubMed

    Klabunde, Anna; Willekens, Frans

    We review agent-based models (ABM) of human migration with respect to their decision-making rules. The most prominent behavioural theories used as decision rules are the random utility theory, as implemented in the discrete choice model, and the theory of planned behaviour. We identify the critical choices that must be made in developing an ABM, namely the modelling of decision processes and social networks. We also discuss two challenges that hamper the widespread use of ABM in the study of migration and, more broadly, demography and the social sciences: (a) the choice and the operationalisation of a behavioural theory (decision-making and social interaction) and (b) the selection of empirical evidence to validate the model. We offer advice on how these challenges might be overcome.

  5. Integrated PK-PD and agent-based modeling in oncology.

    PubMed

    Wang, Zhihui; Butner, Joseph D; Cristini, Vittorio; Deisboeck, Thomas S

    2015-04-01

    Mathematical modeling has become a valuable tool that strives to complement conventional biomedical research modalities in order to predict experimental outcome, generate new medical hypotheses, and optimize clinical therapies. Two specific approaches, pharmacokinetic-pharmacodynamic (PK-PD) modeling, and agent-based modeling (ABM), have been widely applied in cancer research. While they have made important contributions on their own (e.g., PK-PD in examining chemotherapy drug efficacy and resistance, and ABM in describing and predicting tumor growth and metastasis), only a few groups have started to combine both approaches together in an effort to gain more insights into the details of drug dynamics and the resulting impact on tumor growth. In this review, we focus our discussion on some of the most recent modeling studies building on a combined PK-PD and ABM approach that have generated experimentally testable hypotheses. Some future directions are also discussed.

  6. The Evolution of Cooperation in Managed Groundwater Systems: An Agent-Based Modelling Approach

    NASA Astrophysics Data System (ADS)

    Castilla Rho, J. C.; Mariethoz, G.; Rojas, R. F.; Andersen, M. S.; Kelly, B. F.; Holley, C.

    2014-12-01

    Human interactions with groundwater systems often exhibit complex features that hinder the sustainable management of the resource. This leads to costly and persistent conflicts over groundwater at the catchment scale. One possible way to address these conflicts is by gaining a better understanding of how social and groundwater dynamics coevolve using agent-based models (ABM). Such models allow exploring 'bottom-up' solutions (i.e., self-organised governance systems), where the behaviour of individual agents (e.g., farmers) results in the emergence of mutual cooperation among groundwater users. There is significant empirical evidence indicating that this kind of 'bottom-up' approach may lead to more enduring and sustainable outcomes, compared to conventional 'top-down' strategies such as centralized control and water right schemes (Ostrom 1990). New modelling tools are needed to study these concepts systematically and efficiently. Our model uses a conceptual framework to study cooperation and the emergence of social norms as initially proposed by Axelrod (1986), which we adapted to groundwater management. We developed an ABM that integrates social mechanisms and the physics of subsurface flow. The model explicitly represents feedback between groundwater conditions and social dynamics, capturing the spatial structure of these interactions and the potential effects on cooperation levels in an agricultural setting. Using this model, we investigate a series of mechanisms that may trigger norms supporting cooperative strategies, which can be sustained and become stable over time. For example, farmers in a self-monitoring community can be more efficient at achieving the objective of sustainable groundwater use than government-imposed regulation. Our coupled model thus offers a platform for testing new schemes promoting cooperation and improved resource use, which can be used as a basis for policy design. Importantly, we hope to raise awareness of agent-based modelling as

  7. An agent-based simulation model to study accountable care organizations.

    PubMed

    Liu, Pai; Wu, Shinyi

    2016-03-01

    Creating accountable care organizations (ACOs) has been widely discussed as a strategy to control rapidly rising healthcare costs and improve quality of care; however, building an effective ACO is a complex process involving multiple stakeholders (payers, providers, patients) with their own interests. Also, implementation of an ACO is costly in terms of time and money. Immature design could cause safety hazards. Therefore, there is a need for analytical model-based decision-support tools that can predict the outcomes of different strategies to facilitate ACO design and implementation. In this study, an agent-based simulation model was developed to study ACOs that considers payers, healthcare providers, and patients as agents under the shared saving payment model of care for congestive heart failure (CHF), one of the most expensive causes of sometimes preventable hospitalizations. The agent-based simulation model has identified the critical determinants for the payment model design that can motivate provider behavior changes to achieve maximum financial and quality outcomes of an ACO. The results show nonlinear provider behavior change patterns corresponding to changes in payment model designs. The outcomes vary by providers with different quality or financial priorities, and are most sensitive to the cost-effectiveness of CHF interventions that an ACO implements. This study demonstrates an increasingly important method to construct a healthcare system analytics model that can help inform health policy and healthcare management decisions. The study also points out that the likely success of an ACO is interdependent with payment model design, provider characteristics, and cost and effectiveness of healthcare interventions.

  8. High Performance Computing for Agent-Based Cognitive Modeling

    DTIC Science & Technology

    2011-02-25

    enterprise applications, is Common Object Request Broker Architecture ( CORBA ). CORBA provides methods for programming language and platform...independent communication between applications(" CORBA FAQ,"). CORBA works by allowing developers to specify an object using a standardized Interface...Definition Language (IDL), and mapping the IDL to data types available in each language that implements a CORBA library. This is similar in nature to

  9. Spatial structuring and size selection as collective behaviours in an agent-based model for barchan fields

    NASA Astrophysics Data System (ADS)

    Génois, Mathieu; Hersen, Pascal; du Pont, Sylvain Courrech; Grégoire, Guillaume

    2013-11-01

    In order to test parameters of the peculiar dynamics occurring in barchan fields, and compute statistical analysis over large numbers of dunes, we build and study an agent-based model, which includes the well-known physics of an isolated barchan, and observations of interactions between dunes. We showed in a previous study that such a model, where barchans interact through short-range sand recapture and collisions, reproduces the peculiar behaviours of real fields, namely its spatial structuring along the wind direction, and the size selection by the local density. In this paper we focus on the mechanisms that drives these features. In particular, we show that eolian remote sand transfer between dunes ensures that a dense field structures itself into a very heterogeneous pattern, which alternates dense and diluted stripes in the wind direction. In these very dense clusters of dunes, the accumulation of collisions leads to the local emergence of a new size for the dunes.

  10. CystiSim – An Agent-Based Model for Taenia solium Transmission and Control

    PubMed Central

    Gabriël, Sarah; Dorny, Pierre; Speybroeck, Niko; Magnussen, Pascal; Torgerson, Paul; Johansen, Maria Vang

    2016-01-01

    Taenia solium taeniosis/cysticercosis was declared eradicable by the International Task Force for Disease Eradication in 1993, but remains a neglected zoonosis. To assist in the attempt to regionally eliminate this parasite, we developed cystiSim, an agent-based model for T. solium transmission and control. The model was developed in R and available as an R package (http://cran.r-project.org/package=cystiSim). cystiSim was adapted to an observed setting using field data from Tanzania, but adaptable to other settings if necessary. The model description adheres to the Overview, Design concepts, and Details (ODD) protocol and consists of two entities—pigs and humans. Pigs acquire cysticercosis through the environment or by direct contact with a tapeworm carrier's faeces. Humans acquire taeniosis from slaughtered pigs proportional to their infection intensity. The model allows for evaluation of three interventions measures or combinations hereof: treatment of humans, treatment of pigs, and pig vaccination, and allows for customary coverage and efficacy settings. cystiSim is the first agent-based transmission model for T. solium and suggests that control using a strategy consisting of an intervention only targeting the porcine host is possible, but that coverage and efficacy must be high if elimination is the ultimate goal. Good coverage of the intervention is important, but can be compensated for by including an additional intervention targeting the human host. cystiSim shows that the scenarios combining interventions in both hosts, mass drug administration to humans, and vaccination and treatment of pigs, have a high probability of success if coverage of 75% can be maintained over at least a four year period. In comparison with an existing mathematical model for T. solium transmission, cystiSim also includes parasite maturation, host immunity, and environmental contamination. Adding these biological parameters to the model resulted in new insights in the potential

  11. Agent-Based Model with Asymmetric Trading and Herding for Complex Financial Systems

    PubMed Central

    Chen, Jun-Jie; Zheng, Bo; Tan, Lei

    2013-01-01

    Background For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. Methods To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors’ asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. Results With the model parameters determined for six representative stock-market indices in the world, respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. Conclusions We reveal that for the leverage and anti-leverage effects, both the investors’ asymmetric trading and herding are essential generation mechanisms. Among the six markets, however, the investors’ trading is approximately symmetric for the five markets which exhibit the leverage effect, thus contributing very little. These two microscopic mechanisms and the methods for the determination of the key

  12. CystiSim - An Agent-Based Model for Taenia solium Transmission and Control.

    PubMed

    Braae, Uffe Christian; Devleesschauwer, Brecht; Gabriël, Sarah; Dorny, Pierre; Speybroeck, Niko; Magnussen, Pascal; Torgerson, Paul; Johansen, Maria Vang

    2016-12-01

    Taenia solium taeniosis/cysticercosis was declared eradicable by the International Task Force for Disease Eradication in 1993, but remains a neglected zoonosis. To assist in the attempt to regionally eliminate this parasite, we developed cystiSim, an agent-based model for T. solium transmission and control. The model was developed in R and available as an R package (http://cran.r-project.org/package=cystiSim). cystiSim was adapted to an observed setting using field data from Tanzania, but adaptable to other settings if necessary. The model description adheres to the Overview, Design concepts, and Details (ODD) protocol and consists of two entities-pigs and humans. Pigs acquire cysticercosis through the environment or by direct contact with a tapeworm carrier's faeces. Humans acquire taeniosis from slaughtered pigs proportional to their infection intensity. The model allows for evaluation of three interventions measures or combinations hereof: treatment of humans, treatment of pigs, and pig vaccination, and allows for customary coverage and efficacy settings. cystiSim is the first agent-based transmission model for T. solium and suggests that control using a strategy consisting of an intervention only targeting the porcine host is possible, but that coverage and efficacy must be high if elimination is the ultimate goal. Good coverage of the intervention is important, but can be compensated for by including an additional intervention targeting the human host. cystiSim shows that the scenarios combining interventions in both hosts, mass drug administration to humans, and vaccination and treatment of pigs, have a high probability of success if coverage of 75% can be maintained over at least a four year period. In comparison with an existing mathematical model for T. solium transmission, cystiSim also includes parasite maturation, host immunity, and environmental contamination. Adding these biological parameters to the model resulted in new insights in the potential

  13. Agent-based model with asymmetric trading and herding for complex financial systems.

    PubMed

    Chen, Jun-Jie; Zheng, Bo; Tan, Lei

    2013-01-01

    For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors' asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. With the model parameters determined for six representative stock-market indices in the world, respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. We reveal that for the leverage and anti-leverage effects, both the investors' asymmetric trading and herding are essential generation mechanisms. Among the six markets, however, the investors' trading is approximately symmetric for the five markets which exhibit the leverage effect, thus contributing very little. These two microscopic mechanisms and the methods for the determination of the key parameters can be applied to other complex

  14. Evaluating network analysis and agent based modeling for investigating the stability of commercial air carrier schedules

    NASA Astrophysics Data System (ADS)

    Conway, Sheila Ruth

    For a number of years, the United States Federal Government has been formulating the Next Generation Air Transportation System plans for National Airspace System improvement. These improvements attempt to address air transportation holistically, but often address individual improvements in one arena such as ground or in-flight equipment. In fact, air transportation system designers have had only limited success using traditional Operations Research and parametric modeling approaches in their analyses of innovative operations. They need a systemic methodology for modeling of safety-critical infrastructure that is comprehensive, objective, and sufficiently concrete, yet simple enough to be deployed with reasonable investment. The methodology must also be amenable to quantitative analysis so issues of system safety and stability can be rigorously addressed. The literature suggests that both agent-based models and network analysis techniques may be useful for complex system development and analysis. The purpose of this research is to evaluate these two techniques as applied to analysis of commercial air carrier schedule (route) stability in daily operations, an important component of air transportation. Airline-like routing strategies are used to educe essential elements of applying the method. Two main models are developed, one investigating the network properties of the route structure, the other an Agent-based approach. The two methods are used to predict system properties at a macro-level. These findings are compared to observed route network performance measured by adherence to a schedule to provide validation of the results. Those interested in complex system modeling are provided some indication as to when either or both of the techniques would be applicable. For aviation policy makers, the results point to a toolset capable of providing insight into the system behavior during the formative phases of development and transformation with relatively low investment

  15. An agent-based model for queue formation of powered two-wheelers in heterogeneous traffic

    NASA Astrophysics Data System (ADS)

    Lee, Tzu-Chang; Wong, K. I.

    2016-11-01

    This paper presents an agent-based model (ABM) for simulating the queue formation of powered two-wheelers (PTWs) in heterogeneous traffic at a signalized intersection. The main novelty is that the proposed interaction rule describing the position choice behavior of PTWs when queuing in heterogeneous traffic can capture the stochastic nature of the decision making process. The interaction rule is formulated as a multinomial logit model, which is calibrated by using a microscopic traffic trajectory dataset obtained from video footage. The ABM is validated against the survey data for the vehicular trajectory patterns, queuing patterns, queue lengths, and discharge rates. The results demonstrate that the proposed model is capable of replicating the observed queue formation process for heterogeneous traffic.

  16. Minority persistence in agent based model using information and emotional arousal as control variables

    NASA Astrophysics Data System (ADS)

    Sobkowicz, Pawel

    2013-07-01

    We present detailed analysis of the behavior of an agent based model of opinion formation, using a discrete variant of cusp catastrophe behavior of single agents. The agent opinion about a particular issue is determined by its information about the issue and its emotional arousal. It is possible that for agitated agents the same information would lead to different opinions. This results in a nontrivial individual opinion dynamics. The agents communicate via messages, which allows direct application of the model to ICT based communities. We study the dependence of the composition of an agent society on the range of interactions and the rate of emotional arousal. Despite the minimal number of adjustable parameters, the model reproduces several phenomena observed in real societies, for example nearly perfectly balanced results of some highly contested elections or the fact that minorities seldom perceive themselves to be a minority.

  17. An agent based model for simulating the spread of sexually transmitted infections.

    PubMed

    Rutherford, Grant; Friesen, Marcia R; McLeod, Robert D

    2012-01-01

    This work uses agent-based modelling (ABM) to simulate sexually transmitted infection (STIs) spread within a population of 1000 agents over a 10-year period, as a preliminary investigation of the suitability of ABM methodology to simulate STI spread. The work contrasts compartmentalized mathematical models that fail to account for individual agents, and ABMs commonly applied to simulate the spread of respiratory infections. The model was developed in C++ using the Boost 1.47.0 libraries for the normal distribution and OpenGL for visualization. Sixteen agent parameters interact individually and in combination to govern agent profiles and behaviours relative to infection probabilities. The simulation results provide qualitative comparisons of STI mitigation strategies, including the impact of condom use, promiscuity, the form of the friend network, and mandatory STI testing. Individual and population-wide impacts were explored, with individual risk being impacted much more dramatically by population-level behaviour changes as compared to individual behaviour changes.

  18. Agent-Based Model Approach to Complex Phenomena in Real Economy

    NASA Astrophysics Data System (ADS)

    Iyetomi, H.; Aoyama, H.; Fujiwara, Y.; Ikeda, Y.; Souma, W.

    An agent-based model for firms' dynamics is developed. The model consists of firm agents with identical characteristic parameters and a bank agent. Dynamics of those agents are described by their balance sheets. Each firm tries to maximize its expected profit with possible risks in market. Infinite growth of a firm directed by the ``profit maximization" principle is suppressed by a concept of ``going concern". Possibility of bankruptcy of firms is also introduced by incorporating a retardation effect of information on firms' decision. The firms, mutually interacting through the monopolistic bank, become heterogeneous in the course of temporal evolution. Statistical properties of firms' dynamics obtained by simulations based on the model are discussed in light of observations in the real economy.

  19. An agent-based interaction model for Chinese personal income distribution

    NASA Astrophysics Data System (ADS)

    Zou, Yijiang; Deng, Weibing; Li, Wei; Cai, Xu

    2015-10-01

    The personal income distribution in China was studied by employing the data from China Household Income Projects (CHIP) between 1990 and 2002. It was observed that the low and middle income regions could be described by the log-normal law, while the large income region could be well fitted by the power law. To characterize these empirical findings, a stochastic interactive model with mean-field approach was discussed, and the analytic result shows that the wealth distribution is of the Pareto type. Then we explored the agent-based model on networks, in which the exchange of wealth among agents depends on their connectivity. Numerical results suggest that the wealth of agents would largely rely on their connectivity, and the Pareto index of the simulated wealth distributions is comparable to those of the empirical data. The Pareto behavior of the tails of the empirical wealth distributions is consistent with that of the 'mean-field' model, as well as numerical simulations.

  20. Study of the attractor structure of an agent-based sociological model

    NASA Astrophysics Data System (ADS)

    Timpanaro, André M.; Prado, Carmen P. C.

    2011-03-01

    The Sznajd model is a sociophysics model that is based in the Potts model, and used for describing opinion propagation in a society. It employs an agent-based approach and interaction rules favouring pairs of agreeing agents. It has been successfully employed in modeling some properties and scale features of both proportional and majority elections (see for instance the works of A. T. Bernardes and R. N. Costa Filho), but its stationary states are always consensus states. In order to explain more complicated behaviours, we have modified the bounded confidence idea (introduced before in other opinion models, like the Deffuant model), with the introduction of prejudices and biases (we called this modification confidence rules), and have adapted it to the discrete Sznajd model. This generalized Sznajd model is able to reproduce almost all of the previous versions of the Sznajd model, by using appropriate choices of parameters. We solved the attractor structure of the resulting model in a mean-field approach and made Monte Carlo simulations in a Barabási-Albert network. These simulations show great similarities with the mean-field, for the tested cases of 3 and 4 opinions. The dynamical systems approach that we devised allows for a deeper understanding of the potential of the Sznajd model as an opinion propagation model and can be easily extended to other models, like the voter model. Our modification of the bounded confidence rule can also be readily applied to other opinion propagation models.

  1. Agent-Based Modeling of Endotoxin-Induced Acute Inflammatory Response in Human Blood Leukocytes

    PubMed Central

    Dong, Xu; Foteinou, Panagiota T.; Calvano, Steven E.; Lowry, Stephen F.; Androulakis, Ioannis P.

    2010-01-01

    Background Inflammation is a highly complex biological response evoked by many stimuli. A persistent challenge in modeling this dynamic process has been the (nonlinear) nature of the response that precludes the single-variable assumption. Systems-based approaches offer a promising possibility for understanding inflammation in its homeostatic context. In order to study the underlying complexity of the acute inflammatory response, an agent-based framework is developed that models the emerging host response as the outcome of orchestrated interactions associated with intricate signaling cascades and intercellular immune system interactions. Methodology/Principal Findings An agent-based modeling (ABM) framework is proposed to study the nonlinear dynamics of acute human inflammation. The model is implemented using NetLogo software. Interacting agents involve either inflammation-specific molecules or cells essential for the propagation of the inflammatory reaction across the system. Spatial orientation of molecule interactions involved in signaling cascades coupled with the cellular heterogeneity are further taken into account. The proposed in silico model is evaluated through its ability to successfully reproduce a self-limited inflammatory response as well as a series of scenarios indicative of the nonlinear dynamics of the response. Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades. Conclusions/Significance The ABM framework developed in this study provides insight on the stochastic interactions of the mediators involved in the propagation of endotoxin signaling at the cellular response level. The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components. The

  2. Evolving Nutritional Strategies in the Presence of Competition: A Geometric Agent-Based Model

    PubMed Central

    Senior, Alistair M.; Charleston, Michael A.; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J.

    2015-01-01

    Access to nutrients is a key factor governing development, reproduction and ultimately fitness. Within social groups, contest-competition can fundamentally affect nutrient access, potentially leading to reproductive asymmetry among individuals. Previously, agent-based models have been combined with the Geometric Framework of nutrition to provide insight into how nutrition and social interactions affect one another. Here, we expand this modelling approach by incorporating evolutionary algorithms to explore how contest-competition over nutrient acquisition might affect the evolution of animal nutritional strategies. Specifically, we model tolerance of nutrient excesses and deficits when ingesting nutritionally imbalanced foods, which we term ‘nutritional latitude’; a higher degree of nutritional latitude constitutes a higher tolerance of nutritional excess and deficit. Our results indicate that a transition between two alternative strategies occurs at moderate to high levels of competition. When competition is low, individuals display a low level of nutritional latitude and regularly switch foods in search of an optimum. When food is scarce and contest-competition is intense, high nutritional latitude appears optimal, and individuals continue to consume an imbalanced food for longer periods before attempting to switch to an alternative. However, the relative balance of nutrients within available foods also strongly influences at what levels of competition, if any, transitions between these two strategies occur. Our models imply that competition combined with reproductive skew in social groups can play a role in the evolution of diet breadth. We discuss how the integration of agent-based, nutritional and evolutionary modelling may be applied in future studies to further understand the evolution of nutritional strategies across social and ecological contexts. PMID:25815976

  3. Simulating the elimination of sleeping sickness with an agent-based model.

    PubMed

    Grébaut, Pascal; Girardin, Killian; Fédérico, Valentine; Bousquet, François

    2016-01-01

    Although Human African Trypanosomiasis is largely considered to be in the process of extinction today, the persistence of human and animal reservoirs, as well as the vector, necessitates a laborious elimination process. In this context, modeling could be an effective tool to evaluate the ability of different public health interventions to control the disease. Using the Cormas(®) system, we developed HATSim, an agent-based model capable of simulating the possible endemic evolutions of sleeping sickness and the ability of National Control Programs to eliminate the disease. This model takes into account the analysis of epidemiological, entomological, and ecological data from field studies conducted during the last decade, making it possible to predict the evolution of the disease within this area over a 5-year span. In this article, we first present HATSim according to the Overview, Design concepts, and Details (ODD) protocol that is classically used to describe agent-based models, then, in a second part, we present predictive results concerning the evolution of Human African Trypanosomiasis in the village of Lambi (Cameroon), in order to illustrate the interest of such a tool. Our results are consistent with what was observed in the field by the Cameroonian National Control Program (CNCP). Our simulations also revealed that regular screening can be sufficient, although vector control applied to all areas with human activities could be significantly more efficient. Our results indicate that the current model can already help decision-makers in planning the elimination of the disease in foci. © P. Grébaut et al., published by EDP Sciences, 2016.

  4. Agent based model of effects of task allocation strategies in flat organizations

    NASA Astrophysics Data System (ADS)

    Sobkowicz, Pawel

    2016-09-01

    A common practice in many organizations is to pile the work on the best performers. It is easy to implement by the management and, despite the apparent injustice, appears to be working in many situations. In our work we present a simple agent based model, constructed to simulate this practice and to analyze conditions under which the overall efficiency of the organization (for example measured by the backlog of unresolved issues) breaks down, due to the cumulative effect of the individual overloads. The model confirms that the strategy mentioned above is, indeed, rational: it leads to better global results than an alternative one, using equal workload distribution among all workers. The presented analyses focus on the behavior of the organizations close to the limit of the maximum total throughput and provide results for the growth of the unprocessed backlog in several situations, as well as suggestions related to avoiding such buildup.

  5. Determination of the periodicity and synchronization of anticipative agent based supply-demand model

    NASA Astrophysics Data System (ADS)

    Škraba, A.; Bren, M.; Kofjač, D.

    2017-02-01

    The paper presents the transformation of cobweb model by including the anticipation about the supply and demand. Developed transformation leads to oscillatory behaviour. The periodic conditions of the model have been analytically determined by the application of z-transform. Periodic solutions of the system are presented in the form of an inverse Farey tree, where the Golden Ratio path could be observed. The table of periodic conditions is given up to period 8. The agent-based system was developed in order to show the possibility of controlling the system by varying the key parameter, which determines the frequency response of agents and their interaction. A note on application in the stock market has been provided.

  6. An adaptive scheduling model for a multi-agent based VEPR data collection actions.

    PubMed

    Vieira-Marques, Pedro; Jácome, Jorge; Hilário-Patriarca, José; Cruz-Correia, Ricardo

    2015-01-01

    With the purpose of improving the access to departmental legacy information systems, a multi agent based Virtual Electronic Patient Record (VEPR) was deployed at a major Portuguese Hospital. The agent module (MAID) is in charge of identifying new data produced (reports), collecting and making it available through an integrated web interface. The deployed MAID system uses a static interval for checking the existence of new data, however from the gathered data regarding each department data production it is observable a variable rate throughout the day. In order to address this variability an adaptive model was developed and tested in a simulated environment with real data. The model takes in consideration the past report production profiles for determining a variable query frequency in order to reduce the average time to make data available minimizing the number of departmental requests.

  7. Microscopic understanding of heavy-tailed return distributions in an agent-based model

    NASA Astrophysics Data System (ADS)

    Schmitt, Thilo A.; Schäfer, Rudi; Münnix, Michael C.; Guhr, Thomas

    2012-11-01

    The distribution of returns in financial time series exhibits heavy tails. It has been found that gaps between the orders in the order book lead to large price shifts and thereby to these heavy tails. We set up an agent-based model to study this issue and, in particular, how the gaps in the order book emerge. The trading mechanism in our model is based on a double-auction order book. In situations where the order book is densely occupied with limit orders we do not observe fat-tailed distributions. As soon as less liquidity is available, a gap structure forms which leads to return distributions with heavy tails. We show that return distributions with heavy tails are an order-book effect if the available liquidity is constrained. This is largely independent of specific trading strategies.

  8. Skin Stem Cell Hypotheses and Long Term Clone Survival – Explored Using Agent-based Modelling

    PubMed Central

    Li, X.; Upadhyay, A. K.; Bullock, A. J.; Dicolandrea, T.; Xu, J.; Binder, R. L.; Robinson, M. K.; Finlay, D. R.; Mills, K. J.; Bascom, C. C.; Kelling, C. K.; Isfort, R. J.; Haycock, J. W.; MacNeil, S.; Smallwood, R. H.

    2013-01-01

    Epithelial renewal in skin is achieved by the constant turnover and differentiation of keratinocytes. Three popular hypotheses have been proposed to explain basal keratinocyte regeneration and epidermal homeostasis: 1) asymmetric division (stem-transit amplifying cell); 2) populational asymmetry (progenitor cell with stochastic fate); and 3) populational asymmetry with stem cells. In this study, we investigated lineage dynamics using these hypotheses with a 3D agent-based model of the epidermis. The model simulated the growth and maintenance of the epidermis over three years. The offspring of each proliferative cell was traced. While all lineages were preserved in asymmetric division, the vast majority were lost when assuming populational asymmetry. The third hypothesis provided the most reliable mechanism for self-renewal by preserving genetic heterogeneity in quiescent stem cells, and also inherent mechanisms for skin ageing and the accumulation of genetic mutation. PMID:23712735

  9. Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

    SciTech Connect

    Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

    2015-10-30

    An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease states in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.

  10. Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

    DOE PAGES

    Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

    2015-10-30

    An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

  11. Holistic flood risk assessment using agent-based modelling: the case of Sint Maarten Island

    NASA Astrophysics Data System (ADS)

    Abayneh Abebe, Yared; Vojinovic, Zoran; Nikolic, Igor; Hammond, Michael; Sanchez, Arlex; Pelling, Mark

    2015-04-01

    Floods in coastal regions are regarded as one of the most dangerous and harmful disasters. Though commonly referred to as natural disasters, coastal floods are also attributable to various social, economic, historical and political issues. Rapid urbanisation in coastal areas combined with climate change and poor governance can lead to a significant increase in the risk of pluvial flooding coinciding with fluvial and coastal flooding posing a greater risk of devastation in coastal communities. Disasters that can be triggered by hydro-meteorological events are interconnected and interrelated with both human activities and natural processes. They, therefore, require holistic approaches to help understand their complexity in order to design and develop adaptive risk management approaches that minimise social and economic losses and environmental impacts, and increase resilience to such events. Being located in the North Atlantic Ocean, Sint Maarten is frequently subjected to hurricanes. In addition, the stormwater catchments and streams on Sint Maarten have several unique characteristics that contribute to the severity of flood-related impacts. Urban environments are usually situated in low-lying areas, with little consideration for stormwater drainage, and as such are subject to flash flooding. Hence, Sint Maarten authorities drafted policies to minimise the risk of flood-related disasters on the island. In this study, an agent-based model is designed and applied to understand the implications of introduced policies and regulations, and to understand how different actors' behaviours influence the formation, propagation and accumulation of flood risk. The agent-based model built for this study is based on the MAIA meta-model, which helps to decompose, structure and conceptualize socio-technical systems with an agent-oriented perspective, and is developed using the NetLogo simulation environment. The agents described in this model are households and businesses, and

  12. Optimal harvesting for a predator-prey agent-based model using difference equations.

    PubMed

    Oremland, Matthew; Laubenbacher, Reinhard

    2015-03-01

    In this paper, a method known as Pareto optimization is applied in the solution of a multi-objective optimization problem. The system in question is an agent-based model (ABM) wherein global dynamics emerge from local interactions. A system of discrete mathematical equations is formulated in order to capture the dynamics of the ABM; while the original model is built up analytically from the rules of the model, the paper shows how minor changes to the ABM rule set can have a substantial effect on model dynamics. To address this issue, we introduce parameters into the equation model that track such changes. The equation model is amenable to mathematical theory—we show how stability analysis can be performed and validated using ABM data. We then reduce the equation model to a simpler version and implement changes to allow controls from the ABM to be tested using the equations. Cohen's weighted κ is proposed as a measure of similarity between the equation model and the ABM, particularly with respect to the optimization problem. The reduced equation model is used to solve a multi-objective optimization problem via a technique known as Pareto optimization, a heuristic evolutionary algorithm. Results show that the equation model is a good fit for ABM data; Pareto optimization provides a suite of solutions to the multi-objective optimization problem that can be implemented directly in the ABM.

  13. Impact of urban planning on household's residential decisions: An agent-based simulation model for Vienna.

    PubMed

    Gaube, Veronika; Remesch, Alexander

    2013-07-01

    Interest in assessing the sustainability of socio-ecological systems of urban areas has increased notably, with additional attention generated due to the fact that half the world's population now lives in cities. Urban areas face both a changing urban population size and increasing sustainability issues in terms of providing good socioeconomic and environmental living conditions. Urban planning has to deal with both challenges. Households play a major role by being affected by urban planning decisions on the one hand and by being responsible - among many other factors - for the environmental performance of a city (e.g. energy use). We here present an agent-based decision model referring to the city of Vienna, the capital of Austria, with a population of about 1.7 million (2.3 million within the metropolitan area, the latter being more than 25% of Austria's total population). Since the early 1990s, after decades of negative population growth, Vienna has been experiencing a steady increase in population, mainly driven by immigration. The aim of the agent-based decision model is to simulate new residential patterns of different household types based on demographic development and migration scenarios. Model results were used to assess spatial patterns of energy use caused by different household types in the four scenarios (1) conventional urban planning, (2) sustainable urban planning, (3) expensive centre and (4) no green area preference. Outcomes show that changes in preferences of households relating to the presence of nearby green areas have the most important impact on the distribution of households across the small-scaled city area. Additionally, the results demonstrate the importance of the distribution of different household types regarding spatial patterns of energy use.

  14. Impact of urban planning on household's residential decisions: An agent-based simulation model for Vienna☆

    PubMed Central

    Gaube, Veronika; Remesch, Alexander

    2013-01-01

    Interest in assessing the sustainability of socio-ecological systems of urban areas has increased notably, with additional attention generated due to the fact that half the world's population now lives in cities. Urban areas face both a changing urban population size and increasing sustainability issues in terms of providing good socioeconomic and environmental living conditions. Urban planning has to deal with both challenges. Households play a major role by being affected by urban planning decisions on the one hand and by being responsible – among many other factors – for the environmental performance of a city (e.g. energy use). We here present an agent-based decision model referring to the city of Vienna, the capital of Austria, with a population of about 1.7 million (2.3 million within the metropolitan area, the latter being more than 25% of Austria's total population). Since the early 1990s, after decades of negative population growth, Vienna has been experiencing a steady increase in population, mainly driven by immigration. The aim of the agent-based decision model is to simulate new residential patterns of different household types based on demographic development and migration scenarios. Model results were used to assess spatial patterns of energy use caused by different household types in the four scenarios (1) conventional urban planning, (2) sustainable urban planning, (3) expensive centre and (4) no green area preference. Outcomes show that changes in preferences of households relating to the presence of nearby green areas have the most important impact on the distribution of households across the small-scaled city area. Additionally, the results demonstrate the importance of the distribution of different household types regarding spatial patterns of energy use. PMID:27667962

  15. Agent-based models for the emergence and evolution of grammar.

    PubMed

    Steels, Luc

    2016-08-19

    Human languages are extraordinarily complex adaptive systems. They feature intricate hierarchical sound structures, are able to express elaborate meanings and use sophisticated syntactic and semantic structures to relate sound to meaning. What are the cognitive mechanisms that speakers and listeners need to create and sustain such a remarkable system? What is the collective evolutionary dynamics that allows a language to self-organize, become more complex and adapt to changing challenges in expressive power? This paper focuses on grammar. It presents a basic cycle observed in the historical language record, whereby meanings move from lexical to syntactic and then to a morphological mode of expression before returning to a lexical mode, and discusses how we can discover and validate mechanisms that can cause these shifts using agent-based models.This article is part of the themed issue 'The major synthetic evolutionary transitions'.

  16. Projecting Sexual and Injecting HIV Risks into Future Outcomes with Agent-Based Modeling

    NASA Astrophysics Data System (ADS)

    Bobashev, Georgiy V.; Morris, Robert J.; Zule, William A.

    Longitudinal studies of health outcomes for HIV could be very costly cumbersome and not representative of the risk population. Conversely, cross-sectional approaches could be representative but rely on the retrospective information to estimate prevalence and incidence. We present an Agent-based Modeling (ABM) approach where we use behavioral data from a cross-sectional representative study and project the behavior into the future so that the risks of acquiring HIV could be studied in a dynamical/temporal sense. We show how the blend of behavior and contact network factors (sexual, injecting) play the role in the risk of future HIV acquisition and time till obtaining HIV. We show which subjects are the most likely persons to get HIV in the next year, and whom they are likely to infect. We examine how different behaviors are related to the increase or decrease of HIV risks and how to estimate the quantifiable risk measures such as survival HIV free.

  17. [Methodological novelties applied to the anthropology of food: agent-based models and social networks analysis].

    PubMed

    Díaz Córdova, Diego

    2016-01-01

    The aim of this article is to introduce two methodological strategies that have not often been utilized in the anthropology of food: agent-based models and social networks analysis. In order to illustrate these methods in action, two cases based in materials typical of the anthropology of food are presented. For the first strategy, fieldwork carried out in Quebrada de Humahuaca (province of Jujuy, Argentina) regarding meal recall was used, and for the second, elements of the concept of "domestic consumption strategies" applied by Aguirre were employed. The underlying idea is that, given that eating is recognized as a "total social fact" and, therefore, as a complex phenomenon, the methodological approach must also be characterized by complexity. The greater the number of methods utilized (with the appropriate rigor), the better able we will be to understand the dynamics of feeding in the social environment.

  18. Improving an Agent-Based Model by Using Interdisciplinary Approaches for Analyzing Structural Change in Agriculture

    NASA Astrophysics Data System (ADS)

    Appel, Franziska; Ostermeyer, Arlette; Balmann, Alfons; Larsen, Karin

    Structural change in the German dairy sector seems to be lagged behind. Heterogeneous farm structures, a low efficiency and profitability are persistent although farms operate under similar market and policy conditions. This raises the questions whether these structures are path dependent and how they can eventually be overcome. To answer these questions we use the agent-based model AgriPoliS. The aim of our project is to improve assumptions in AgriPoliS by using it as an experimental laboratory. In a second part AgriPoliS will be used in stakeholder workshops to define scenarios for the dairy sector and communicate and discuss results to practitioners and decision makers.

  19. Agent-based models for the emergence and evolution of grammar

    PubMed Central

    2016-01-01

    Human languages are extraordinarily complex adaptive systems. They feature intricate hierarchical sound structures, are able to express elaborate meanings and use sophisticated syntactic and semantic structures to relate sound to meaning. What are the cognitive mechanisms that speakers and listeners need to create and sustain such a remarkable system? What is the collective evolutionary dynamics that allows a language to self-organize, become more complex and adapt to changing challenges in expressive power? This paper focuses on grammar. It presents a basic cycle observed in the historical language record, whereby meanings move from lexical to syntactic and then to a morphological mode of expression before returning to a lexical mode, and discusses how we can discover and validate mechanisms that can cause these shifts using agent-based models. This article is part of the themed issue ‘The major synthetic evolutionary transitions’. PMID:27431525

  20. Agent-based modeling of a multi-room multi-floor building emergency evacuation

    NASA Astrophysics Data System (ADS)

    Ha, Vi; Lykotrafitis, George

    2012-04-01

    Panic during emergency building evacuation can cause crowd stampede, resulting in serious injuries and casualties. Agent-based methods have been successfully employed to investigate the collective human behavior during emergency evacuation in cases where the configurational space is extremely simple-usually one rectangular room-but not in evacuations of multi-room or multi-floor buildings. This implies that the effect of the complexity of building architecture on the collective behavior of the agents during evacuation has not been fully investigated. Here, we employ a system of self-moving particles whose motion is governed by the social-force model to investigate the effect of complex building architecture on the uncoordinated crowd motion during urgent evacuation. In particular, we study how the room door size, the size of the main exit, the desired speed and the friction coefficient affect the evacuation time and under what circumstances the evacuation efficiency improves.

  1. Re-Examining of Moffitt’s Theory of Delinquency through Agent Based Modeling

    PubMed Central

    Leaw, Jia Ning; Ang, Rebecca P.; Huan, Vivien S.; Chan, Wei Teng; Cheong, Siew Ann

    2015-01-01

    Moffitt’s theory of delinquency suggests that at-risk youths can be divided into two groups, the adolescence- limited group and the life-course-persistent group, predetermined at a young age, and social interactions between these two groups become important during the adolescent years. We built an agent-based model based on the microscopic interactions Moffitt described: (i) a maturity gap that dictates (ii) the cost and reward of antisocial behavior, and (iii) agents imitating the antisocial behaviors of others more successful than themselves, to find indeed the two groups emerging in our simulations. Moreover, through an intervention simulation where we moved selected agents from one social network to another, we also found that the social network plays an important role in shaping the life course outcome. PMID:26062022

  2. Re-Examining of Moffitt's Theory of Delinquency through Agent Based Modeling.

    PubMed

    Leaw, Jia Ning; Ang, Rebecca P; Huan, Vivien S; Chan, Wei Teng; Cheong, Siew Ann

    2015-01-01

    Moffitt's theory of delinquency suggests that at-risk youths can be divided into two groups, the adolescence- limited group and the life-course-persistent group, predetermined at a young age, and social interactions between these two groups become important during the adolescent years. We built an agent-based model based on the microscopic interactions Moffitt described: (i) a maturity gap that dictates (ii) the cost and reward of antisocial behavior, and (iii) agents imitating the antisocial behaviors of others more successful than themselves, to find indeed the two groups emerging in our simulations. Moreover, through an intervention simulation where we moved selected agents from one social network to another, we also found that the social network plays an important role in shaping the life course outcome.

  3. The Evolution of ICT Markets: An Agent-Based Model on Complex Networks

    NASA Astrophysics Data System (ADS)

    Zhao, Liangjie; Wu, Bangtao; Chen, Zhong; Li, Li

    Information and communication technology (ICT) products exhibit positive network effects.The dynamic process of ICT markets evolution has two intrinsic characteristics: (1) customers are influenced by each others’ purchasing decision; (2) customers are intelligent agents with bounded rationality.Guided by complex systems theory, we construct an agent-based model and simulate on complex networks to examine how the evolution can arise from the interaction of customers, which occur when they make expectations about the future installed base of a product by the fraction of neighbors who are using the same product in his personal network.We demonstrate that network effects play an important role in the evolution of markets share, which make even an inferior product can dominate the whole market.We also find that the intensity of customers’ communication can influence whether the best initial strategy for firms is to improve product quality or expand their installed base.

  4. Combination HIV prevention among MSM in South Africa: results from agent-based modeling.

    PubMed

    Brookmeyer, Ron; Boren, David; Baral, Stefan D; Bekker, Linda-Gail; Phaswana-Mafuya, Nancy; Beyrer, Chris; Sullivan, Patrick S

    2014-01-01

    HIV prevention trials have demonstrated the effectiveness of a number of behavioral and biomedical interventions. HIV prevention packages are combinations of interventions and offer potential to significantly increase the effectiveness of any single intervention. Estimates of the effectiveness of prevention packages are important for guiding the development of prevention strategies and for characterizing effect sizes before embarking on large scale trials. Unfortunately, most research to date has focused on testing single interventions rather than HIV prevention packages. Here we report the results from agent-based modeling of the effectiveness of HIV prevention packages for men who have sex with men (MSM) in South Africa. We consider packages consisting of four components: antiretroviral therapy for HIV infected persons with CD4 count <350; PrEP for high risk uninfected persons; behavioral interventions to reduce rates of unprotected anal intercourse (UAI); and campaigns to increase HIV testing. We considered 163 HIV prevention packages corresponding to different intensity levels of the four components. We performed 2252 simulation runs of our agent-based model to evaluate those packages. We found that a four component package consisting of a 15% reduction in the rate of UAI, 50% PrEP coverage of high risk uninfected persons, 50% reduction in persons who never test for HIV, and 50% ART coverage over and above persons already receiving ART at baseline, could prevent 33.9% of infections over 5 years (95% confidence interval, 31.5, 36.3). The package components with the largest incremental prevention effects were UAI reduction and PrEP coverage. The impact of increased HIV testing was magnified in the presence of PrEP. We find that HIV prevention packages that include both behavioral and biomedical components can in combination prevent significant numbers of infections with levels of coverage, acceptance and adherence that are potentially achievable among MSM in

  5. `Models of' versus `Models for'. Toward an Agent-Based Conception of Modeling in the Science Classroom

    NASA Astrophysics Data System (ADS)

    Gouvea, Julia; Passmore, Cynthia

    2017-03-01

    The inclusion of the practice of "developing and using models" in the Framework for K-12 Science Education and in the Next Generation Science Standards provides an opportunity for educators to examine the role this practice plays in science and how it can be leveraged in a science classroom. Drawing on conceptions of models in the philosophy of science, we bring forward an agent-based account of models and discuss the implications of this view for enacting modeling in science classrooms. Models, according to this account, can only be understood with respect to the aims and intentions of a cognitive agent (models for), not solely in terms of how they represent phenomena in the world (models of). We present this contrast as a heuristic— models of versus models for—that can be used to help educators notice and interpret how models are positioned in standards, curriculum, and classrooms.

  6. Identity in agent-based models : modeling dynamic multiscale social processes.

    SciTech Connect

    Ozik, J.; Sallach, D. L.; Macal, C. M.; Decision and Information Sciences; Univ. of Chicago

    2008-07-01

    Identity-related issues play central roles in many current events, including those involving factional politics, sectarianism, and tribal conflicts. Two popular models from the computational-social-science (CSS) literature - the Threat Anticipation Program and SharedID models - incorporate notions of identity (individual and collective) and processes of identity formation. A multiscale conceptual framework that extends some ideas presented in these models and draws other capabilities from the broader CSS literature is useful in modeling the formation of political identities. The dynamic, multiscale processes that constitute and transform social identities can be mapped to expressive structures of the framework

  7. An agent-based hydroeconomic model to evaluate water policies in Jordan

    NASA Astrophysics Data System (ADS)

    Yoon, J.; Gorelick, S.

    2014-12-01

    Modern water systems can be characterized by a complex network of institutional and private actors that represent competing sectors and interests. Identifying solutions to enhance water security in such systems calls for analysis that can adequately account for this level of complexity and interaction. Our work focuses on the development of a hierarchical, multi-agent, hydroeconomic model that attempts to realistically represent complex interactions between hydrologic and multi-faceted human systems. The model is applied to Jordan, one of the most water-poor countries in the world. In recent years, the water crisis in Jordan has escalated due to an ongoing drought and influx of refugees from regional conflicts. We adopt a modular approach in which biophysical modules simulate natural and engineering phenomena, and human modules represent behavior at multiple scales of decision making. The human modules employ agent-based modeling, in which agents act as autonomous decision makers at the transboundary, state, organizational, and user levels. A systematic nomenclature and conceptual framework is used to characterize model agents and modules. Concepts from the Unified Modeling Language (UML) are adopted to promote clear conceptualization of model classes and process sequencing, establishing a foundation for full deployment of the integrated model in a scalable object-oriented programming environment. Although the framework is applied to the Jordanian water context, it is generalizable to other regional human-natural freshwater supply systems.

  8. A standard protocol for describing individual-based and agent-based models

    USGS Publications Warehouse

    Grimm, Volker; Berger, Uta; Bastiansen, Finn; Eliassen, Sigrunn; Ginot, Vincent; Giske, Jarl; Goss-Custard, John; Grand, Tamara; Heinz, Simone K.; Huse, Geir; Huth, Andreas; Jepsen, Jane U.; Jorgensen, Christian; Mooij, Wolf M.; Muller, Birgit; Pe'er, Guy; Piou, Cyril; Railsback, Steven F.; Robbins, Andrew M.; Robbins, Martha M.; Rossmanith, Eva; Ruger, Nadja; Strand, Espen; Souissi, Sami; Stillman, Richard A.; Vabo, Rune; Visser, Ute; DeAngelis, Donald L.

    2006-01-01

    Simulation models that describe autonomous individual organisms (individual based models, IBM) or agents (agent-based models, ABM) have become a widely used tool, not only in ecology, but also in many other disciplines dealing with complex systems made up of autonomous entities. However, there is no standard protocol for describing such simulation models, which can make them difficult to understand and to duplicate. This paper presents a proposed standard protocol, ODD, for describing IBMs and ABMs, developed and tested by 28 modellers who cover a wide range of fields within ecology. This protocol consists of three blocks (Overview, Design concepts, and Details), which are subdivided into seven elements: Purpose, State variables and scales, Process overview and scheduling, Design concepts, Initialization, Input, and Submodels. We explain which aspects of a model should be described in each element, and we present an example to illustrate the protocol in use. In addition, 19 examples are available in an Online Appendix. We consider ODD as a first step for establishing a more detailed common format of the description of IBMs and ABMs. Once initiated, the protocol will hopefully evolve as it becomes used by a sufficiently large proportion of modellers.

  9. Using simple agent-based modeling to inform and enhance neighborhood walkability

    PubMed Central

    2013-01-01

    Background Pedestrian-friendly neighborhoods with proximal destinations and services encourage walking and decrease car dependence, thereby contributing to more active and healthier communities. Proximity to key destinations and services is an important aspect of the urban design decision making process, particularly in areas adopting a transit-oriented development (TOD) approach to urban planning, whereby densification occurs within walking distance of transit nodes. Modeling destination access within neighborhoods has been limited to circular catchment buffers or more sophisticated network-buffers generated using geoprocessing routines within geographical information systems (GIS). Both circular and network-buffer catchment methods are problematic. Circular catchment models do not account for street networks, thus do not allow exploratory ‘what-if’ scenario modeling; and network-buffering functionality typically exists within proprietary GIS software, which can be costly and requires a high level of expertise to operate. Methods This study sought to overcome these limitations by developing an open-source simple agent-based walkable catchment tool that can be used by researchers, urban designers, planners, and policy makers to test scenarios for improving neighborhood walkable catchments. A simplified version of an agent-based model was ported to a vector-based open source GIS web tool using data derived from the Australian Urban Research Infrastructure Network (AURIN). The tool was developed and tested with end-user stakeholder working group input. Results The resulting model has proven to be effective and flexible, allowing stakeholders to assess and optimize the walkability of neighborhood catchments around actual or potential nodes of interest (e.g., schools, public transport stops). Users can derive a range of metrics to compare different scenarios modeled. These include: catchment area versus circular buffer ratios; mean number of streets crossed; and

  10. Using simple agent-based modeling to inform and enhance neighborhood walkability.

    PubMed

    Badland, Hannah; White, Marcus; Macaulay, Gus; Eagleson, Serryn; Mavoa, Suzanne; Pettit, Christopher; Giles-Corti, Billie

    2013-12-11

    Pedestrian-friendly neighborhoods with proximal destinations and services encourage walking and decrease car dependence, thereby contributing to more active and healthier communities. Proximity to key destinations and services is an important aspect of the urban design decision making process, particularly in areas adopting a transit-oriented development (TOD) approach to urban planning, whereby densification occurs within walking distance of transit nodes. Modeling destination access within neighborhoods has been limited to circular catchment buffers or more sophisticated network-buffers generated using geoprocessing routines within geographical information systems (GIS). Both circular and network-buffer catchment methods are problematic. Circular catchment models do not account for street networks, thus do not allow exploratory 'what-if' scenario modeling; and network-buffering functionality typically exists within proprietary GIS software, which can be costly and requires a high level of expertise to operate. This study sought to overcome these limitations by developing an open-source simple agent-based walkable catchment tool that can be used by researchers, urban designers, planners, and policy makers to test scenarios for improving neighborhood walkable catchments. A simplified version of an agent-based model was ported to a vector-based open source GIS web tool using data derived from the Australian Urban Research Infrastructure Network (AURIN). The tool was developed and tested with end-user stakeholder working group input. The resulting model has proven to be effective and flexible, allowing stakeholders to assess and optimize the walkability of neighborhood catchments around actual or potential nodes of interest (e.g., schools, public transport stops). Users can derive a range of metrics to compare different scenarios modeled. These include: catchment area versus circular buffer ratios; mean number of streets crossed; and modeling of different walking

  11. Acceptability of an Embodied Conversational Agent-based Computer Application for Hispanic Women

    PubMed Central

    Wells, Kristen J.; Vázquez-Otero, Coralia; Bredice, Marissa; Meade, Cathy D.; Chaet, Alexis; Rivera, Maria I.; Arroyo, Gloria; Proctor, Sara K.; Barnes, Laura E.

    2015-01-01

    There are few Spanish language interactive, technology-driven health education programs. Objectives of this feasibility study were to: 1) learn more about computer and technology usage among Hispanic women living in a rural community; and 2) evaluate acceptability of the concept of using an embodied conversational agent (ECA) computer application among this population. A survey about computer usage history and interest in computers was administered to a convenience sample of 26 women. A sample video prototype of a hospital discharge ECA was administered followed by questions to gauge opinion about the ECA. Data indicate women exhibited both a high level of computer experience and enthusiasm for the ECA. Feedback from community is essential to ensure equity in state of the art dissemination of health information. Hay algunos programas interactivos en español que usan la tecnología para educar sobre la salud. Los objetivos de este estudio fueron: 1) aprender más sobre el uso de computadoras y tecnología entre mujeres Hispanas que viven en comunidades rurales y 2) evaluar la aceptabilidad del concepto de usar un programa de computadora utilizando un agente de conversación encarnado (ECA) en esta población. Se administro una encuesta sobre el historial de uso y del interés de aprender sobre computadoras fue a 26 mujeres por muestreo de conveniencia. Un ejemplo del prototipo ECA en forma de video de un alta hospitalaria fue administrado y fue seguido por preguntas sobre la opinión que tenían del ECA. Los datos indican que las mujeres mostraron un alto nivel de experiencia con las computadoras y un alto nivel de entusiasmo sobre el ECA. La retroalimentación de la comunidad es esencial para asegurar equidad en la diseminación de información sobre la salud con tecnología de punta. PMID:26671558

  12. POLARIS: Agent-Based Modeling Framework Development and Implementation for Integrated Travel Demand and Network and Operations Simulations

    SciTech Connect

    Auld, Joshua; Hope, Michael; Ley, Hubert; Sokolov, Vadim; Xu, Bo; Zhang, Kuilin

    2016-03-01

    This paper discusses the development of an agent-based modelling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations. A description is given of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine, and memory allocator, as well as a number of ancillary utilities: visualization library, database IO library, and scenario manager. The overall framework emphasizes the design goals of: generality, code agility, and high performance. This framework allows the modeling of several aspects of transportation system that are typically done with separate stand-alone software applications, in a high-performance and extensible manner. The issue of integrating such models as dynamic traffic assignment and disaggregate demand models has been a long standing issue for transportation modelers. The integrated approach shows a possible way to resolve this difficulty. The simulation model built from the POLARIS framework is a single, shared-memory process for handling all aspects of the integrated urban simulation. The resulting gains in computational efficiency and performance allow planning models to be extended to include previously separate aspects of the urban system, enhancing the utility of such models from the planning perspective. Initial tests with case studies involving traffic management center impacts on various network events such as accidents, congestion and weather events, show the potential of the system.

  13. Friendship Network and Dental Brushing Behavior among Middle School Students: An Agent Based Modeling Approach

    PubMed Central

    Sadeghipour, Maryam; Khoshnevisan, Mohammad Hossein; Jafari, Afshin; Shariatpanahi, Seyed Peyman

    2017-01-01

    By using a standard questionnaire, the level of dental brushing frequency was assessed among 201 adolescent female middle school students in Tehran. The initial assessment was repeated after 5 months, in order to observe the dynamics in dental health behavior level. Logistic Regression model was used to evaluate the correlation among individuals’ dental health behavior in their social network. A significant correlation on dental brushing habits was detected among groups of friends. This correlation was further spread over the network within the 5 months period. Moreover, it was identified that the average brushing level was improved within the 5 months period. Given that there was a significant correlation between social network’s nodes’ in-degree value, and brushing level, it was suggested that the observed improvement was partially due to more popularity of individuals with better tooth brushing habit. Agent Based Modeling (ABM) was used to demonstrate the dynamics of dental brushing frequency within a sample of friendship network. Two models with static and dynamic assumptions for the network structure were proposed. The model with dynamic network structure successfully described the dynamics of dental health behavior. Based on this model, on average, every 43 weeks a student changes her brushing habit due to learning from her friends. Finally, three training scenarios were tested by these models in order to evaluate their effectiveness. When training more popular students, considerable improvement in total students’ brushing frequency was demonstrated by simulation results. PMID:28103260

  14. Friendship Network and Dental Brushing Behavior among Middle School Students: An Agent Based Modeling Approach.

    PubMed

    Sadeghipour, Maryam; Khoshnevisan, Mohammad Hossein; Jafari, Afshin; Shariatpanahi, Seyed Peyman

    2017-01-01

    By using a standard questionnaire, the level of dental brushing frequency was assessed among 201 adolescent female middle school students in Tehran. The initial assessment was repeated after 5 months, in order to observe the dynamics in dental health behavior level. Logistic Regression model was used to evaluate the correlation among individuals' dental health behavior in their social network. A significant correlation on dental brushing habits was detected among groups of friends. This correlation was further spread over the network within the 5 months period. Moreover, it was identified that the average brushing level was improved within the 5 months period. Given that there was a significant correlation between social network's nodes' in-degree value, and brushing level, it was suggested that the observed improvement was partially due to more popularity of individuals with better tooth brushing habit. Agent Based Modeling (ABM) was used to demonstrate the dynamics of dental brushing frequency within a sample of friendship network. Two models with static and dynamic assumptions for the network structure were proposed. The model with dynamic network structure successfully described the dynamics of dental health behavior. Based on this model, on average, every 43 weeks a student changes her brushing habit due to learning from her friends. Finally, three training scenarios were tested by these models in order to evaluate their effectiveness. When training more popular students, considerable improvement in total students' brushing frequency was demonstrated by simulation results.

  15. An agent-based model of stock markets incorporating momentum investors

    NASA Astrophysics Data System (ADS)

    Wei, J. R.; Huang, J. P.; Hui, P. M.

    2013-06-01

    It has been widely accepted that there exist investors who adopt momentum strategies in real stock markets. Understanding the momentum behavior is of both academic and practical importance. For this purpose, we propose and study a simple agent-based model of trading incorporating momentum investors and random investors. The random investors trade randomly all the time. The momentum investors could be idle, buying or selling, and they decide on their action by implementing an action threshold that assesses the most recent price movement. The model is able to reproduce some of the stylized facts observed in real markets, including the fat-tails in returns, weak long-term correlation and scaling behavior in the kurtosis of returns. An analytic treatment of the model relates the model parameters to several quantities that can be extracted from real data sets. To illustrate how the model can be applied, we show that real market data can be used to constrain the model parameters, which in turn provide information on the behavior of momentum investors in different markets.

  16. Quantitative Agent Based Model of Opinion Dynamics: Polish Elections of 2015

    PubMed Central

    Sobkowicz, Pawel

    2016-01-01

    We present results of an abstract, agent based model of opinion dynamics simulations based on the emotion/information/opinion (E/I/O) approach, applied to a strongly polarized society, corresponding to the Polish political scene between 2005 and 2015. Under certain conditions the model leads to metastable coexistence of two subcommunities of comparable size (supporting the corresponding opinions)—which corresponds to the bipartisan split found in Poland. Spurred by the recent breakdown of this political duopoly, which occurred in 2015, we present a model extension that describes both the long term coexistence of the two opposing opinions and a rapid, transitory change due to the appearance of a third party alternative. We provide quantitative comparison of the model with the results of polls and elections in Poland, testing the assumptions related to the modeled processes and the parameters used in the simulations. It is shown, that when the propaganda messages of the two incumbent parties differ in emotional tone, the political status quo may be unstable. The asymmetry of the emotions within the support bases of the two parties allows one of them to be ‘invaded’ by a newcomer third party very quickly, while the second remains immune to such invasion. PMID:27171226

  17. Integrating Household Risk Mitigation Behavior in Flood Risk Analysis: An Agent-Based Model Approach.

    PubMed

    Haer, Toon; Botzen, W J Wouter; de Moel, Hans; Aerts, Jeroen C J H

    2016-11-28

    Recent studies showed that climate change and socioeconomic trends are expected to increase flood risks in many regions. However, in these studies, human behavior is commonly assumed to be constant, which neglects interaction and feedback loops between human and environmental systems. This neglect of human adaptation leads to a misrepresentation of flood risk. This article presents an agent-based model that incorporates human decision making in flood risk analysis. In particular, household investments in loss-reducing measures are examined under three economic decision models: (1) expected utility theory, which is the traditional economic model of rational agents; (2) prospect theory, which takes account of bounded rationality; and (3) a prospect theory model, which accounts for changing risk perceptions and social interactions through a process of Bayesian updating. We show that neglecting human behavior in flood risk assessment studies can result in a considerable misestimation of future flood risk, which is in our case study an overestimation of a factor two. Furthermore, we show how behavior models can support flood risk analysis under different behavioral assumptions, illustrating the need to include the dynamic adaptive human behavior of, for instance, households, insurers, and governments. The method presented here provides a solid basis for exploring human behavior and the resulting flood risk with respect to low-probability/high-impact risks.

  18. Designing novel cellulase systems through agent-based modeling and global sensitivity analysis

    PubMed Central

    Apte, Advait A; Senger, Ryan S; Fong, Stephen S

    2014-01-01

    Experimental techniques allow engineering of biological systems to modify functionality; however, there still remains a need to develop tools to prioritize targets for modification. In this study, agent-based modeling (ABM) was used to build stochastic models of complexed and non-complexed cellulose hydrolysis, including enzymatic mechanisms for endoglucanase, exoglucanase, and β-glucosidase activity. Modeling results were consistent with experimental observations of higher efficiency in complexed systems than non-complexed systems and established relationships between specific cellulolytic mechanisms and overall efficiency. Global sensitivity analysis (GSA) of model results identified key parameters for improving overall cellulose hydrolysis efficiency including: (1) the cellulase half-life, (2) the exoglucanase activity, and (3) the cellulase composition. Overall, the following parameters were found to significantly influence cellulose consumption in a consolidated bioprocess (CBP): (1) the glucose uptake rate of the culture, (2) the bacterial cell concentration, and (3) the nature of the cellulase enzyme system (complexed or non-complexed). Broadly, these results demonstrate the utility of combining modeling and sensitivity analysis to identify key parameters and/or targets for experimental improvement. PMID:24830736

  19. Putting agent-based modeling to work: results of the 4th International Project Albert Workshop

    NASA Astrophysics Data System (ADS)

    Horne, Gary E.; Bjorkman, Eileen A.; Colton, Trevor

    2002-07-01

    Project Albert is an initiative of the US Marine Corps which uses a series of new models and tools, multidisciplinary teams, and the scientific method to explore questions of interest to military planners. Project Albert attempts to address key areas that traditional modeling and simulation techniques often do not capture satisfactorily and uses two data management concepts, data farming and data mining, to assist in identifying areas of interest. The current suite of models used by Project Albert includes four agent-based models that allow agents to interact with each other and produce emergent behaviors. The 4th International Project Albert Workshop was held 6-9 August 2001 in Australia. Workshop participants split into five groups, each of which attempted to apply various combinations of the Project Albert models to answer a series of questions in five areas: Control Operations; Reconnaissance, Surveillance, and Intelligence Force Mix; Precision Maneuver; Mission Area Analysis; and Peace Support Operations. This paper focuses on the methodology used during the workshop, the results of the workshop, and a summary of follow-on work since the workshop.

  20. Designing novel cellulase systems through agent-based modeling and global sensitivity analysis.

    PubMed

    Apte, Advait A; Senger, Ryan S; Fong, Stephen S

    2014-01-01

    Experimental techniques allow engineering of biological systems to modify functionality; however, there still remains a need to develop tools to prioritize targets for modification. In this study, agent-based modeling (ABM) was used to build stochastic models of complexed and non-complexed cellulose hydrolysis, including enzymatic mechanisms for endoglucanase, exoglucanase, and β-glucosidase activity. Modeling results were consistent with experimental observations of higher efficiency in complexed systems than non-complexed systems and established relationships between specific cellulolytic mechanisms and overall efficiency. Global sensitivity analysis (GSA) of model results identified key parameters for improving overall cellulose hydrolysis efficiency including: (1) the cellulase half-life, (2) the exoglucanase activity, and (3) the cellulase composition. Overall, the following parameters were found to significantly influence cellulose consumption in a consolidated bioprocess (CBP): (1) the glucose uptake rate of the culture, (2) the bacterial cell concentration, and (3) the nature of the cellulase enzyme system (complexed or non-complexed). Broadly, these results demonstrate the utility of combining modeling and sensitivity analysis to identify key parameters and/or targets for experimental improvement.

  1. Minimal agent based model for financial markets II. Statistical properties of the linear and multiplicative dynamics

    NASA Astrophysics Data System (ADS)

    Alfi, V.; Cristelli, M.; Pietronero, L.; Zaccaria, A.

    2009-02-01

    We present a detailed study of the statistical properties of the Agent Based Model introduced in paper I [Eur. Phys. J. B, DOI: 10.1140/epjb/e2009-00028-4] and of its generalization to the multiplicative dynamics. The aim of the model is to consider the minimal elements for the understanding of the origin of the stylized facts and their self-organization. The key elements are fundamentalist agents, chartist agents, herding dynamics and price behavior. The first two elements correspond to the competition between stability and instability tendencies in the market. The herding behavior governs the possibility of the agents to change strategy and it is a crucial element of this class of models. We consider a linear approximation for the price dynamics which permits a simple interpretation of the model dynamics and, for many properties, it is possible to derive analytical results. The generalized non linear dynamics results to be extremely more sensible to the parameter space and much more difficult to analyze and control. The main results for the nature and self-organization of the stylized facts are, however, very similar in the two cases. The main peculiarity of the non linear dynamics is an enhancement of the fluctuations and a more marked evidence of the stylized facts. We will also discuss some modifications of the model to introduce more realistic elements with respect to the real markets.

  2. Stimulating household flood risk mitigation investments through insurance and subsidies: an Agent-Based Modelling approach

    NASA Astrophysics Data System (ADS)

    Haer, Toon; Botzen, Wouter; de Moel, Hans; Aerts, Jeroen

    2015-04-01

    In the period 1998-2009, floods triggered roughly 52 billion euro in insured economic losses making floods the most costly natural hazard in Europe. Climate change and socio/economic trends are expected to further aggrevate floods losses in many regions. Research shows that flood risk can be significantly reduced if households install protective measures, and that the implementation of such measures can be stimulated through flood insurance schemes and subsidies. However, the effectiveness of such incentives to stimulate implementation of loss-reducing measures greatly depends on the decision process of individuals and is hardly studied. In our study, we developed an Agent-Based Model that integrates flood damage models, insurance mechanisms, subsidies, and household behaviour models to assess the effectiveness of different economic tools on stimulating households to invest in loss-reducing measures. Since the effectiveness depends on the decision making process of individuals, the study compares different household decision models ranging from standard economic models, to economic models for decision making under risk, to more complex decision models integrating economic models and risk perceptions, opinion dynamics, and the influence of flood experience. The results show the effectiveness of incentives to stimulate investment in loss-reducing measures for different household behavior types, while assuming climate change scenarios. It shows how complex decision models can better reproduce observed real-world behaviour compared to traditional economic models. Furthermore, since flood events are included in the simulations, the results provide an analysis of the dynamics in insured and uninsured losses for households, the costs of reducing risk by implementing loss-reducing measures, the capacity of the insurance market, and the cost of government subsidies under different scenarios. The model has been applied to the City of Rotterdam in The Netherlands.

  3. Partner choice promotes cooperation: the two faces of testing with agent-based models.

    PubMed

    Campennì, Marco; Schino, Gabriele

    2014-03-07

    Reciprocity is one of the most debated among the mechanisms that have been proposed to explain the evolution of cooperation. While a distinction can be made between two general processes that can underlie reciprocation (within-pair temporal relations between cooperative events, and partner choice based on benefits received), theoretical modelling has concentrated on the former, while the latter has been often neglected. We developed a set of agent-based models in which agents adopted a strategy of obligate cooperation and partner choice based on benefits received. Our models tested the ability of partner choice both to reproduce significant emergent features of cooperation in group living animals and to promote the evolution of cooperation. Populations formed by agents adopting a strategy of obligate cooperation and partner choice based on benefits received showed differentiated "social relationships" and a positive correlation between cooperation given and received, two common phenomena in animal cooperation. When selection across multiple generations was added to the model, agents adopting a strategy of partner choice based on benefits received outperformed selfish agents that did not cooperate. Our results suggest partner choice is a significant aspect of cooperation and provides a possible mechanism for its evolution.

  4. Multiple phase transitions in an agent-based evolutionary model with neutral fitness.

    PubMed

    King, Dawn M; Scott, Adam D; Bahar, Sonya

    2017-04-01

    Null models are crucial for understanding evolutionary processes such as speciation and adaptive radiation. We analyse an agent-based null model, considering a case without selection-neutral evolution-in which organisms are defined only by phenotype. Universal dynamics has previously been demonstrated in a related model on a neutral fitness landscape, showing that this system belongs to the directed percolation (DP) universality class. The traditional null condition of neutral fitness (where fitness is defined as the number of offspring each organism produces) is extended here to include equal probability of death among organisms. We identify two types of phase transition: (i) a non-equilibrium DP transition through generational time (i.e. survival), and (ii) an equilibrium ordinary percolation transition through the phenotype space (based on links between mating organisms). Owing to the dynamical rules of the DP reaction-diffusion process, organisms can only sparsely fill the phenotype space, resulting in significant phenotypic diversity within a cluster of mating organisms. This highlights the necessity of understanding hierarchical evolutionary relationships, rather than merely developing taxonomies based on phenotypic similarity, in order to develop models that can explain phylogenetic patterns found in the fossil record or to make hypotheses for the incomplete fossil record of deep time.

  5. Multiple phase transitions in an agent-based evolutionary model with neutral fitness

    PubMed Central

    Scott, Adam D.; Bahar, Sonya

    2017-01-01

    Null models are crucial for understanding evolutionary processes such as speciation and adaptive radiation. We analyse an agent-based null model, considering a case without selection—neutral evolution—in which organisms are defined only by phenotype. Universal dynamics has previously been demonstrated in a related model on a neutral fitness landscape, showing that this system belongs to the directed percolation (DP) universality class. The traditional null condition of neutral fitness (where fitness is defined as the number of offspring each organism produces) is extended here to include equal probability of death among organisms. We identify two types of phase transition: (i) a non-equilibrium DP transition through generational time (i.e. survival), and (ii) an equilibrium ordinary percolation transition through the phenotype space (based on links between mating organisms). Owing to the dynamical rules of the DP reaction–diffusion process, organisms can only sparsely fill the phenotype space, resulting in significant phenotypic diversity within a cluster of mating organisms. This highlights the necessity of understanding hierarchical evolutionary relationships, rather than merely developing taxonomies based on phenotypic similarity, in order to develop models that can explain phylogenetic patterns found in the fossil record or to make hypotheses for the incomplete fossil record of deep time. PMID:28484629

  6. An agent-based approach to modelling the effects of extreme events on global food prices

    NASA Astrophysics Data System (ADS)

    Schewe, Jacob; Otto, Christian; Frieler, Katja

    2015-04-01

    Extreme climate events such as droughts or heat waves affect agricultural production in major food producing regions and therefore can influence the price of staple foods on the world market. There is evidence that recent dramatic spikes in grain prices were at least partly triggered by actual and/or expected supply shortages. The reaction of the market to supply changes is however highly nonlinear and depends on complex and interlinked processes such as warehousing, speculation, and export restrictions. Here we present for the first time an agent-based modelling framework that accounts, in simplified terms, for these processes and allows to estimate the reaction of world food prices to supply shocks on a short (monthly) timescale. We test the basic model using observed historical supply, demand, and price data of wheat as a major food grain. Further, we illustrate how the model can be used in conjunction with biophysical crop models to assess the effect of future changes in extreme event regimes on the volatility of food prices. In particular, the explicit representation of storage dynamics makes it possible to investigate the potentially nonlinear interaction between simultaneous extreme events in different food producing regions, or between several consecutive events in the same region, which may both occur more frequently under future global warming.

  7. An agent-based model of dialect evolution in killer whales.

    PubMed

    Filatova, Olga A; Miller, Patrick J O

    2015-05-21

    The killer whale is one of the few animal species with vocal dialects that arise from socially learned group-specific call repertoires. We describe a new agent-based model of killer whale populations and test a set of vocal-learning rules to assess which mechanisms may lead to the formation of dialect groupings observed in the wild. We tested a null model with genetic transmission and no learning, and ten models with learning rules that differ by template source (mother or matriline), variation type (random errors or innovations) and type of call change (no divergence from kin vs. divergence from kin). The null model without vocal learning did not produce the pattern of group-specific call repertoires we observe in nature. Learning from either mother alone or the entire matriline with calls changing by random errors produced a graded distribution of the call phenotype, without the discrete call types observed in nature. Introducing occasional innovation or random error proportional to matriline variance yielded more or less discrete and stable call types. A tendency to diverge from the calls of related matrilines provided fast divergence of loose call clusters. A pattern resembling the dialect diversity observed in the wild arose only when rules were applied in combinations and similar outputs could arise from different learning rules and their combinations. Our results emphasize the lack of information on quantitative features of wild killer whale dialects and reveal a set of testable questions that can draw insights into the cultural evolution of killer whale dialects.

  8. Towards a Hybrid Agent-based Model for Mosquito Borne Disease.

    PubMed

    Mniszewski, S M; Manore, C A; Bryan, C; Del Valle, S Y; Roberts, D

    2014-07-01

    Agent-based models (ABM) are used to simulate the spread of infectious disease through a population. Detailed human movement, demography, realistic business location networks, and in-host disease progression are available in existing ABMs, such as the Epidemic Simulation System (EpiSimS). These capabilities make possible the exploration of pharmaceutical and non-pharmaceutical mitigation strategies used to inform the public health community. There is a similar need for the spread of mosquito borne pathogens due to the re-emergence of diseases such as chikungunya and dengue fever. A network-patch model for mosquito dynamics has been coupled with EpiSimS. Mosquitoes are represented as a "patch" or "cloud" associated with a location. Each patch has an ordinary differential equation (ODE) mosquito dynamics model and mosquito related parameters relevant to the location characteristics. Activities at each location can have different levels of potential exposure to mosquitoes based on whether they are inside, outside, or somewhere in-between. As a proof of concept, the hybrid network-patch model is used to simulate the spread of chikungunya through Washington, DC. Results are shown for a base case, followed by varying the probability of transmission, mosquito count, and activity exposure. We use visualization to understand the pattern of disease spread.

  9. Patterns of Use of an Agent-Based Model and a System Dynamics Model: The Application of Patterns of Use and the Impacts on Learning Outcomes

    ERIC Educational Resources Information Center

    Thompson, Kate; Reimann, Peter

    2010-01-01

    A classification system that was developed for the use of agent-based models was applied to strategies used by school-aged students to interrogate an agent-based model and a system dynamics model. These were compared, and relationships between learning outcomes and the strategies used were also analysed. It was found that the classification system…

  10. The Hunt Opinion Model-An Agent Based Approach to Recurring Fashion Cycles.

    PubMed

    Apriasz, Rafał; Krueger, Tyll; Marcjasz, Grzegorz; Sznajd-Weron, Katarzyna

    2016-01-01

    We study a simple agent-based model of the recurring fashion cycles in the society that consists of two interacting communities: "snobs" and "followers" (or "opinion hunters", hence the name of the model). Followers conform to all other individuals, whereas snobs conform only to their own group and anticonform to the other. The model allows to examine the role of the social structure, i.e. the influence of the number of inter-links between the two communities, as well as the role of the stability of links. The latter is accomplished by considering two versions of the same model-quenched (parameterized by fraction L of fixed inter-links) and annealed (parameterized by probability p that a given inter-link exists). Using Monte Carlo simulations and analytical treatment (the latter only for the annealed model), we show that there is a critical fraction of inter-links, above which recurring cycles occur. For p ≤ 0.5 we derive a relation between parameters L and p that allows to compare both models and show that the critical value of inter-connections, p*, is the same for both versions of the model (annealed and quenched) but the period of a fashion cycle is shorter for the quenched model. Near the critical point, the cycles are irregular and a change of fashion is difficult to predict. For the annealed model we also provide a deeper theoretical analysis. We conjecture on topological grounds that the so-called saddle node heteroclinic bifurcation appears at p*. For p ≥ 0.5 we show analytically the existence of the second critical value of p, for which the system undergoes Hopf's bifurcation.

  11. Reverse engineering a social agent-based hidden markov model--visage.

    PubMed

    Chen, Hung-Ching Justin; Goldberg, Mark; Magdon-Ismail, Malik; Wallace, William A

    2008-12-01

    We present a machine learning approach to discover the agent dynamics that drives the evolution of the social groups in a community. We set up the problem by introducing an agent-based hidden Markov model for the agent dynamics: an agent's actions are determined by micro-laws. Nonetheless, We learn the agent dynamics from the observed communications without knowing state transitions. Our approach is to identify the appropriate micro-laws corresponding to an identification of the appropriate parameters in the model. The model identification problem is then formulated as a mixed optimization problem. To solve the problem, we develop a multistage learning process for determining the group structure, the group evolution, and the micro-laws of a community based on the observed set of communications among actors, without knowing the semantic contents. Finally, to test the quality of our approximations and the feasibility of the approach, we present the results of extensive experiments on synthetic data as well as the results on real communities, such as Enron email and Movie newsgroups. Insight into agent dynamics helps us understand the driving forces behind social evolution.

  12. Buying on margin, selling short in an agent-based market model

    NASA Astrophysics Data System (ADS)

    Zhang, Ting; Li, Honggang

    2013-09-01

    Credit trading, or leverage trading, which includes buying on margin and selling short, plays an important role in financial markets, where agents tend to increase their leverages for increased profits. This paper presents an agent-based asset market model to study the effect of the permissive leverage level on traders’ wealth and overall market indicators. In this model, heterogeneous agents can assume fundamental value-converging expectations or trend-persistence expectations, and their effective demands of assets depend both on demand willingness and wealth constraints, where leverage can relieve the wealth constraints to some extent. The asset market price is determined by a market maker, who watches the market excess demand, and is influenced by noise factors. By simulations, we examine market results for different leverage ratios. At the individual level, we focus on how the leverage ratio influences agents’ wealth accumulation. At the market level, we focus on how the leverage ratio influences changes in the asset price, volatility, and trading volume. Qualitatively, our model provides some meaningful results supported by empirical facts. More importantly, we find a continuous phase transition as we increase the leverage threshold, which may provide a further prospective of credit trading.

  13. Using Agent-Based Models to Develop Public Policy about Food Behaviours: Future Directions and Recommendations

    PubMed Central

    Crutzen, Rik

    2017-01-01

    Most adults are overweight or obese in many western countries. Several population-level interventions on the physical, economical, political, or sociocultural environment have thus attempted to achieve a healthier weight. These interventions have involved different weight-related behaviours, such as food behaviours. Agent-based models (ABMs) have the potential to help policymakers evaluate food behaviour interventions from a systems perspective. However, fully realizing this potential involves a complex procedure starting with obtaining and analyzing data to populate the model and eventually identifying more efficient cross-sectoral policies. Current procedures for ABMs of food behaviours are mostly rooted in one technique, often ignore the food environment beyond home and work, and underutilize rich datasets. In this paper, we address some of these limitations to better support policymakers through two contributions. First, via a scoping review, we highlight readily available datasets and techniques to deal with these limitations independently. Second, we propose a three steps' process to tackle all limitations together and discuss its use to develop future models for food behaviours. We acknowledge that this integrated process is a leap forward in ABMs. However, this long-term objective is well-worth addressing as it can generate robust findings to effectively inform the design of food behaviour interventions. PMID:28421127

  14. Coupling Agent-Based and Groundwater Modeling to Explore Demand Management Strategies for Shared Resources

    NASA Astrophysics Data System (ADS)

    Al-Amin, S.

    2015-12-01

    Municipal water demands in growing population centers in the arid southwest US are typically met through increased groundwater withdrawals. Hydro-climatic uncertainties attributed to climate change and land use conversions may also alter demands and impact the replenishment of groundwater supply. Groundwater aquifers are not necessarily confined within municipal and management boundaries, and multiple diverse agencies may manage a shared resource in a decentralized approach, based on individual concerns and resources. The interactions among water managers, consumers, and the environment influence the performance of local management strategies and regional groundwater resources. This research couples an agent-based modeling (ABM) framework and a groundwater model to analyze the effects of different management approaches on shared groundwater resources. The ABM captures the dynamic interactions between household-level consumers and policy makers to simulate water demands under climate change and population growth uncertainties. The groundwater model is used to analyze the relative effects of management approaches on reducing demands and replenishing groundwater resources. The framework is applied for municipalities located in the Verde River Basin, Arizona that withdraw groundwater from the Verde Formation-Basin Fill-Carbonate aquifer system. Insights gained through this simulation study can be used to guide groundwater policy-making under changing hydro-climatic scenarios for a long-term planning horizon.

  15. Agent-based model with multi-level herding for complex financial systems

    NASA Astrophysics Data System (ADS)

    Chen, Jun-Jie; Tan, Lei; Zheng, Bo

    2015-02-01

    In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

  16. Ising-like agent-based technology diffusion model: Adoption patterns vs. seeding strategies

    NASA Astrophysics Data System (ADS)

    Laciana, Carlos E.; Rovere, Santiago L.

    2011-03-01

    The well-known Ising model used in statistical physics was adapted to a social dynamics context to simulate the adoption of a technological innovation. The model explicitly combines (a) an individual's perception of the advantages of an innovation and (b) social influence from members of the decision-maker's social network. The micro-level adoption dynamics are embedded into an agent-based model that allows exploration of macro-level patterns of technology diffusion throughout systems with different configurations (number and distributions of early adopters, social network topologies). In the present work we carry out many numerical simulations. We find that when the gap between the individual's perception of the options is high, the adoption speed increases if the dispersion of early adopters grows. Another test was based on changing the network topology by means of stochastic connections to a common opinion reference (hub), which resulted in an increment in the adoption speed. Finally, we performed a simulation of competition between options for both regular and small world networks.

  17. Agent-based model with multi-level herding for complex financial systems.

    PubMed

    Chen, Jun-Jie; Tan, Lei; Zheng, Bo

    2015-02-11

    In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

  18. Minimal agent based model for financial markets I. Origin and self-organization of stylized facts

    NASA Astrophysics Data System (ADS)

    Alfi, V.; Cristelli, M.; Pietronero, L.; Zaccaria, A.

    2009-02-01

    We introduce a minimal agent based model for financial markets to understand the nature and self-organization of the stylized facts. The model is minimal in the sense that we try to identify the essential ingredients to reproduce the most important deviations of price time series from a random walk behavior. We focus on four essential ingredients: fundamentalist agents which tend to stabilize the market; chartist agents which induce destabilization; analysis of price behavior for the two strategies; herding behavior which governs the possibility of changing strategy. Bubbles and crashes correspond to situations dominated by chartists, while fundamentalists provide a long time stability (on average). The stylized facts are shown to correspond to an intermittent behavior which occurs only for a finite value of the number of agents N. Therefore they correspond to finite size effects which, however, can occur at different time scales. We propose a new mechanism for the self-organization of this state which is linked to the existence of a threshold for the agents to be active or not active. The feedback between price fluctuations and number of active agents represents a crucial element for this state of self-organized intermittency. The model can be easily generalized to consider more realistic variants.

  19. Agent-based model with multi-level herding for complex financial systems

    PubMed Central

    Chen, Jun-Jie; Tan, Lei; Zheng, Bo

    2015-01-01

    In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level. PMID:25669427

  20. A CSP-Based Agent Modeling Framework for the Cougaar Agent-Based Architecture

    NASA Technical Reports Server (NTRS)

    Gracanin, Denis; Singh, H. Lally; Eltoweissy, Mohamed; Hinchey, Michael G.; Bohner, Shawn A.

    2005-01-01

    Cognitive Agent Architecture (Cougaar) is a Java-based architecture for large-scale distributed agent-based applications. A Cougaar agent is an autonomous software entity with behaviors that represent a real-world entity (e.g., a business process). A Cougaar-based Model Driven Architecture approach, currently under development, uses a description of system's functionality (requirements) to automatically implement the system in Cougaar. The Communicating Sequential Processes (CSP) formalism is used for the formal validation of the generated system. Two main agent components, a blackboard and a plugin, are modeled as CSP processes. A set of channels represents communications between the blackboard and individual plugins. The blackboard is represented as a CSP process that communicates with every agent in the collection. The developed CSP-based Cougaar modeling framework provides a starting point for a more complete formal verification of the automatically generated Cougaar code. Currently it is used to verify the behavior of an individual agent in terms of CSP properties and to analyze the corresponding Cougaar society.

  1. Evolutionary Agent-based Models to design distributed water management strategies

    NASA Astrophysics Data System (ADS)

    Giuliani, M.; Castelletti, A.; Reed, P. M.

    2012-12-01

    There is growing awareness in the scientific community that the traditional centralized approach to water resources management, as described in much of the water resources literature, provides an ideal optimal solution, which is certainly useful to quantify the best physically achievable performance, but is generally inapplicable. Most real world water resources management problems are indeed characterized by the presence of multiple, distributed and institutionally-independent decision-makers. Multi-Agent Systems provide a potentially more realistic alternative framework to model multiple and self-interested decision-makers in a credible context. Each decision-maker can be represented by an agent who, being self-interested, acts according to local objective functions and produces negative externalities on system level objectives. Different levels of coordination can potentially be included in the framework by designing coordination mechanisms to drive the current decision-making structure toward the global system efficiency. Yet, the identification of effective coordination strategies can be particularly complex in modern institutional contexts and current practice is dependent on largely ad-hoc coordination strategies. In this work we propose a novel Evolutionary Agent-based Modeling (EAM) framework that enables a mapping of fully uncoordinated and centrally coordinated solutions into their relative "many-objective" tradeoffs using multiobjective evolutionary algorithms. Then, by analysing the conflicts between local individual agent and global system level objectives it is possible to more fully understand the causes, consequences, and potential solution strategies for coordination failures. Game-theoretic criteria have value for identifying the most interesting alternatives from a policy making point of view as well as the coordination mechanisms that can be applied to obtain these interesting solutions. The proposed approach is numerically tested on a

  2. A framework for the use of agent based modeling to simulate ...

    EPA Pesticide Factsheets

    Simulation of human behavior in exposure modeling is a complex task. Traditionally, inter-individual variation in human activity has been modeled by drawing from a pool of single day time-activity diaries such as the US EPA Consolidated Human Activity Database (CHAD). Here, an agent-based model (ABM) is used to simulate population distributions of longitudinal patterns of four macro activities (sleeping, eating, working, and commuting) in populations of adults over a period of one year. In this ABM, an individual is modeled as an agent whose movement through time and space is determined by a set of decision rules. The rules are based on the agent having time-varying “needs” that are satisfied by performing actions. Needs are modeled as increasing over time, and taking an action reduces the need. Need-satisfying actions include sleeping (meeting the need for rest), eating (meeting the need for food), and commuting/working (meeting the need for income). Every time an action is completed, the model determines the next action the agent will take based on the magnitude of each of the agent’s needs at that point in time. Different activities advertise their ability to satisfy various needs of the agent (such as food to eat or sleeping in a bed or on a couch). The model then chooses the activity that satisfies the greatest of the agent’s needs. When multiple actions could address a need, the model will choose the most effective of the actions (bed over the couc

  3. A framework for the use of agent based modeling to simulate ...

    EPA Pesticide Factsheets

    Simulation of human behavior in exposure modeling is a complex task. Traditionally, inter-individual variation in human activity has been modeled by drawing from a pool of single day time-activity diaries such as the US EPA Consolidated Human Activity Database (CHAD). Here, an agent-based model (ABM) is used to simulate population distributions of longitudinal patterns of four macro activities (sleeping, eating, working, and commuting) in populations of adults over a period of one year. In this ABM, an individual is modeled as an agent whose movement through time and space is determined by a set of decision rules. The rules are based on the agent having time-varying “needs” that are satisfied by performing actions. Needs are modeled as increasing over time, and taking an action reduces the need. Need-satisfying actions include sleeping (meeting the need for rest), eating (meeting the need for food), and commuting/working (meeting the need for income). Every time an action is completed, the model determines the next action the agent will take based on the magnitude of each of the agent’s needs at that point in time. Different activities advertise their ability to satisfy various needs of the agent (such as food to eat or sleeping in a bed or on a couch). The model then chooses the activity that satisfies the greatest of the agent’s needs. When multiple actions could address a need, the model will choose the most effective of the actions (bed over the couc

  4. Optimization and Control of Agent-Based Models in Biology: A Perspective.

    PubMed

    An, G; Fitzpatrick, B G; Christley, S; Federico, P; Kanarek, A; Neilan, R Miller; Oremland, M; Salinas, R; Laubenbacher, R; Lenhart, S

    2017-01-01

    Agent-based models (ABMs) have become an increasingly important mode of inquiry for the life sciences. They are particularly valuable for systems that are not understood well enough to build an equation-based model. These advantages, however, are counterbalanced by the difficulty of analyzing and using ABMs, due to the lack of the type of mathematical tools available for more traditional models, which leaves simulation as the primary approach. As models become large, simulation becomes challenging. This paper proposes a novel approach to two mathematical aspects of ABMs, optimization and control, and it presents a few first steps outlining how one might carry out this approach. Rather than viewing the ABM as a model, it is to be viewed as a surrogate for the actual system. For a given optimization or control problem (which may change over time), the surrogate system is modeled instead, using data from the ABM and a modeling framework for which ready-made mathematical tools exist, such as differential equations, or for which control strategies can explored more easily. Once the optimization problem is solved for the model of the surrogate, it is then lifted to the surrogate and tested. The final step is to lift the optimization solution from the surrogate system to the actual system. This program is illustrated with published work, using two relatively simple ABMs as a demonstration, Sugarscape and a consumer-resource ABM. Specific techniques discussed include dimension reduction and approximation of an ABM by difference equations as well systems of PDEs, related to certain specific control objectives. This demonstration illustrates the very challenging mathematical problems that need to be solved before this approach can be realistically applied to complex and large ABMs, current and future. The paper outlines a research program to address them.

  5. A methodology for eliciting, representing, and analysing stakeholder knowledge for decision making on complex socio-ecological systems: from cognitive maps to agent-based models.

    PubMed

    Elsawah, Sondoss; Guillaume, Joseph H A; Filatova, Tatiana; Rook, Josefine; Jakeman, Anthony J

    2015-03-15

    This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders (qualitative) into formal simulation models (quantitative) with the ultimate goal of improving understanding and communication about decision making in complex socio-ecological systems. The methodology integrates cognitive mapping and agent based modelling. It cascades through a sequence of qualitative/soft and numerical methods comprising: (1) Interviews to elicit mental models; (2) Cognitive maps to represent and analyse individual and group mental models; (3) Time-sequence diagrams to chronologically structure the decision making process; (4) All-encompassing conceptual model of decision making, and (5) computational (in this case agent-based) Model. We apply the proposed methodology (labelled ICTAM) in a case study of viticulture irrigation in South Australia. Finally, we use strengths-weakness-opportunities-threats (SWOT) analysis to reflect on the methodology. Results show that the methodology leverages the use of cognitive mapping to capture the richness of decision making and mental models, and provides a combination of divergent and convergent analysis methods leading to the construction of an Agent Based Model.

  6. Agent based modeling of "crowdinforming" as a means of load balancing at emergency departments.

    PubMed

    Neighbour, Ryan; Oppenheimer, Luis; Mukhi, Shamir N; Friesen, Marcia R; McLeod, Robert D

    2010-01-01

    This work extends ongoing development of a framework for modeling the spread of contact-transmission infectious diseases. The framework is built upon Agent Based Modeling (ABM), with emphasis on urban scale modelling integrated with institutional models of hospital emergency departments. The method presented here includes ABM modeling an outbreak of influenza-like illness (ILI) with concomitant surges at hospital emergency departments, and illustrates the preliminary modeling of 'crowdinforming' as an intervention. 'Crowdinforming', a component of 'crowdsourcing', is characterized as the dissemination of collected and processed information back to the 'crowd' via public access. The objective of the simulation is to allow for effective policy evaluation to better inform the public of expected wait times as part of their decision making process in attending an emergency department or clinic. In effect, this is a means of providing additional decision support garnered from a simulation, prior to real world implementation. The conjecture is that more optimal service delivery can be achieved under balanced patient loads, compared to situations where some emergency departments are overextended while others are underutilized. Load balancing optimization is a common notion in many operations, and the simulation illustrates that 'crowdinforming' is a potential tool when used as a process control parameter to balance the load at emergency departments as well as serving as an effective means to direct patients during an ILI outbreak with temporary clinics deployed. The information provided in the 'crowdinforming' model is readily available in a local context, although it requires thoughtful consideration in its interpretation. The extension to a wider dissemination of information via a web service is readily achievable and presents no technical obstacles, although political obstacles may be present. The 'crowdinforming' simulation is not limited to arrivals of patients at

  7. Testing an agent-based model of bacterial cell motility: How nutrient concentration affects speed distribution

    NASA Astrophysics Data System (ADS)

    Garcia, V.; Birbaumer, M.; Schweitzer, F.

    2011-08-01

    We revisit a recently proposed agent-based model of active biological motion and compare its predictions with own experimental findings for the speed distribution of bacterial cells, Salmonella typhimurium. Agents move according to a stochastic dynamics and use energy stored in an internal depot for metabolism and active motion. We discuss different assumptions of how the conversion from internal to kinetic energy d( v) may depend on the actual speed, to conclude that d 2 v ξ with either ξ = 2 or 1 < ξ < 2 are promising hypotheses. To test these, we compare the model's prediction with the speed distribution of bacteria which were obtained in media of different nutrient concentration and at different times. We find that both hypotheses are in line with the experimental observations, with ξ between 1.67 and 2.0. Regarding the influence of a higher nutrient concentration, we conclude that the take-up of energy by bacterial cells is indeed increased. But this energy is not used to increase the speed, with 40 μm/s as the most probable value of the speed distribution, but is rather spend on metabolism and growth.

  8. The Influence of Seasonal Forecast Accuracy on Farmer Behavior: An Agent-Based Modeling Approach

    NASA Astrophysics Data System (ADS)

    Jacobi, J. H.; Nay, J.; Gilligan, J. M.

    2013-12-01

    Seasonal climates dictate the livelihoods of farmers in developing countries. While farmers in developed countries often have seasonal forecasts on which to base their cropping decisions, developing world farmers usually make plans for the season without such information. Climate change increases the seasonal uncertainty, making things more difficult for farmers. Providing seasonal forecasts to these farmers is seen as a way to help buffer these typically marginal groups from the effects of climate change, though how to do so and the efficacy of such an effort is still uncertain. In Sri Lanka, an effort is underway to provide such forecasts to farmers. The accuracy of these forecasts is likely to have large impacts on how farmers accept and respond to the information they receive. We present an agent-based model to explore how the accuracy of seasonal rainfall forecasts affects the growing decisions and behavior of farmers in Sri Lanka. Using a decision function based on prospect theory, this model simulates farmers' behavior in the face of a wet, dry, or normal forecast. Farmers can either choose to grow paddy rice or plant a cash crop. Prospect theory is used to evaluate outcomes of the growing season; the farmer's memory of the level of success under a certain set of conditions affects next season's decision. Results from this study have implications for policy makers and seasonal forecasters.

  9. An agent-based model of exposure to human toxocariasis: a multi-country validation.

    PubMed

    Kanobana, K; Devleesschauwer, B; Polman, K; Speybroeck, N

    2013-07-01

    Seroprevalence data illustrate that human exposure to Toxocara is frequent. Environmental contamination with Toxocara spp. eggs is assumed to be the best indicator of human exposure, but increased risk of exposure has also been associated with many other factors. Reported associations are inconsistent, however, and there is still ambiguity regarding the factors driving the onset of Toxocara antibody positivity. The objective of this work was to assess the validity of our current conceptual understanding of the key processes driving human exposure to Toxocara. We constructed an agent-based model predicting Toxocara antibody positivity (as a measure of exposure) in children. Exposure was assumed to depend on the joint probability of 3 parameters: (1) environmental contamination with Toxocara spp. eggs, (2) larvation of these eggs and (3) the age-related contact with these eggs. This joint probability was linked to processes of acquired humoral immunity, influencing the rate of antibody seroreversion. The results of the simulation were validated against published data from 5 different geographical settings. Using simple rules and a stochastic approach with parameter estimates derived from the respective contexts, plausible serological patterns emerged from the model in nearly all settings. Our approach leads to novel insights in the transmission dynamics of Toxocara.

  10. Temporal asymmetries in Interbank Market: an empirically grounded Agent-Based Model

    NASA Astrophysics Data System (ADS)

    Zlatic, Vinko; Popovic, Marko; Abraham, Hrvoje; Caldarelli, Guido; Iori, Giulia

    2014-03-01

    We analyse the changes in the topology of the structure of the E-mid interbank market in the period from September 1st 1999 to September 1st 2009. We uncover a type of temporal irreversibility in the growth of the largest component of the interbank trading network, which is not common to any of the usual network growth models. Such asymmetry, which is also detected on the growth of the clustering and reciprocity coefficient, reveals that the trading mechanism is driven by different dynamics at the beginning and at the end of the day. We are able to recover the complexity of the system by means of a simple Agent Based Model in which the probability of matching between counter parties depends on a time varying vertex fitness (or attractiveness) describing banks liquidity needs. We show that temporal irreversibility is associated with heterogeneity in the banking system and emerges when the distribution of liquidity shocks across banks is broad. We acknowledge support from FET project FOC-II.

  11. Retail Location Choice with Complementary Goods: An Agent-Based Model

    NASA Astrophysics Data System (ADS)

    Huang, Arthur; Levinson, David

    This paper models the emergence of retail clusters on a supply chain network comprised of suppliers, retailers, and consumers. Firstly, an agent-based model is proposed to investigate retail location distribution in a market of two complementary goods. The methodology controls for supplier locales and unit sales prices of retailers and suppliers, and a consumer’s willingness to patronize a retailer depends on the total travel distance of buying both goods. On a circle comprised of discrete locations, retailers play a non-cooperative game of location choice to maximize individual profits. Our findings suggest that the probability distribution of the number of clusters in equilibrium follows power law and that hierarchical distribution patterns are much more likely to occur than the spread-out ones. In addition, retailers of complementary goods tend to co-locate at supplier locales. Sensitivity tests on the number of retailers are also performed. Secondly, based on the County Business Patterns (CBP) data of Minneapolis-St. Paul from US Census 2000 database, we find that the number of clothing stores and the distribution of food stores at the zip code level follows power-law distribution.

  12. An Exploratory Study of the Butterfly Effect Using Agent-Based Modeling

    NASA Technical Reports Server (NTRS)

    Khasawneh, Mahmoud T.; Zhang, Jun; Shearer, Nevan E. N.; Rodriquez-Velasquez, Elkin; Bowling, Shannon R.

    2010-01-01

    This paper provides insights about the behavior of chaotic complex systems, and the sensitive dependence of the system on the initial starting conditions. How much does a small change in the initial conditions of a complex system affect it in the long term? Do complex systems exhibit what is called the "Butterfly Effect"? This paper uses an agent-based modeling approach to address these questions. An existing model from NetLogo library was extended in order to compare chaotic complex systems with near-identical initial conditions. Results show that small changes in initial starting conditions can have a huge impact on the behavior of chaotic complex systems. The term the "butterfly effect" is attributed to the work of Edward Lorenz [1]. It is used to describe the sensitive dependence of the behavior of chaotic complex systems on the initial conditions of these systems. The metaphor refers to the notion that a butterfly flapping its wings somewhere may cause extreme changes in the ecological system's behavior in the future, such as a hurricane.

  13. Provider dismissal policies and clustering of vaccine-hesitant families: an agent-based modeling approach.

    PubMed

    Buttenheim, Alison M; Cherng, Sarah T; Asch, David A

    2013-08-01

    Many pediatric practices have adopted vaccine policies that require parents who refuse to vaccinate according to the ACIP schedule to find another health care provider. Such policies may inadvertently cluster unvaccinated patients into practices that tolerate non vaccination or alternative schedules, turning them into risky pockets of low herd immunity. The objective of this study was to assess the effect of provider zero-tolerance vaccination policies on the clustering of intentionally unvaccinated children. We developed an agent-based model of parental vaccine hesitancy, provider non-vaccination tolerance, and selection of patients into pediatric practices. We ran 84 experiments across a range of parental hesitancy and provider tolerance scenarios. When the model is initialized, all providers accommodate refusals and intentionally unvaccinated children are evenly distributed across providers. As provider tolerance decreases, hesitant children become more clustered in a smaller number of practices and eventually are not able to find a practice that will accept them. Each of these effects becomes more pronounced as the level of hesitancy in the population rises. Heterogeneity in practice tolerance to vaccine-hesitant parents has the unintended result of concentrating susceptible individuals within a small number of tolerant practices, while providing little if any compensatory protection to adherent individuals. These externalities suggest an agenda for stricter policy regulation of individual practice decisions.

  14. Using Uncertainty and Sensitivity Analyses in Socioecological Agent-Based Models to Improve Their Analytical Performance and Policy Relevance

    PubMed Central

    Ligmann-Zielinska, Arika; Kramer, Daniel B.; Spence Cheruvelil, Kendra; Soranno, Patricia A.

    2014-01-01

    Agent-based models (ABMs) have been widely used to study socioecological systems. They are useful for studying such systems because of their ability to incorporate micro-level behaviors among interacting agents, and to understand emergent phenomena due to these interactions. However, ABMs are inherently stochastic and require proper handling of uncertainty. We propose a simulation framework based on quantitative uncertainty and sensitivity analyses to build parsimonious ABMs that serve two purposes: exploration of the outcome space to simulate low-probability but high-consequence events that may have significant policy implications, and explanation of model behavior to describe the system with higher accuracy. The proposed framework is applied to the problem of modeling farmland conservation resulting in land use change. We employ output variance decomposition based on quasi-random sampling of the input space and perform three computational experiments. First, we perform uncertainty analysis to improve model legitimacy, where the distribution of results informs us about the expected value that can be validated against independent data, and provides information on the variance around this mean as well as the extreme results. In our last two computational experiments, we employ sensitivity analysis to produce two simpler versions of the ABM. First, input space is reduced only to inputs that produced the variance of the initial ABM, resulting in a model with output distribution similar to the initial model. Second, we refine the value of the most influential input, producing a model that maintains the mean of the output of initial ABM but with less spread. These simplifications can be used to 1) efficiently explore model outcomes, including outliers that may be important considerations in the design of robust policies, and 2) conduct explanatory analysis that exposes the smallest number of inputs influencing the steady state of the modeled system. PMID:25340764

  15. Using participatory agent-based models to measure flood managers' decision thresholds in extreme event response

    NASA Astrophysics Data System (ADS)

    Metzger, A.; Douglass, E.; Gray, S. G.

    2016-12-01

    Extreme flooding impacts to coastal cities are not only a function of storm characteristics, but are heavily influenced by decision-making and preparedness in event-level response. While recent advances in climate and hydrological modeling make it possible to predict the influence of climate change on storm and flooding patterns, flood managers still face a great deal of uncertainty related to adapting organizational responses and decision thresholds to these changing conditions. Some decision thresholds related to mitigation of extreme flood impacts are well-understood and defined by organizational protocol, but others are difficult to quantify due to reliance on contextual expert knowledge, experience, and complexity of information necessary to make certain decisions. Our research attempts to address this issue by demonstrating participatory modeling methods designed to help flood managers (1) better understand and parameterize local decision thresholds in extreme flood management situations, (2) collectively learn about scaling management decision thresholds to future local flooding scenarios and (3) identify effective strategies for adaptating flood mitigation actions and organizational response to climate change-intensified flooding. Our agent-based system dynamic models rely on expert knowledge from local flood managers and sophisticated, climate change-informed hydrological models to simulate current and future flood scenarios. Local flood managers from interact with these models by receiving dynamic information and making management decisions as a flood scenario progresses, allowing parametrization of decision thresholds under different scenarios. Flooding impacts are calculated in each iteration as a means of discussing effectiveness of responses and prioritizing response alternatives. We discuss the findings of this participatory modeling and educational process from a case study of Boston, MA, and discuss transferability of these methods to other types

  16. Using participatory agent-based models to measure flood managers' decision thresholds in extreme event response

    NASA Astrophysics Data System (ADS)

    Metzger, A.; Douglass, E.; Gray, S. G.

    2016-02-01

    Extreme flooding impacts to coastal cities are not only a function of storm characteristics, but are heavily influenced by decision-making and preparedness in event-level response. While recent advances in climate and hydrological modeling make it possible to predict the influence of climate change on storm and flooding patterns, flood managers still face a great deal of uncertainty related to adapting organizational responses and decision thresholds to these changing conditions. Some decision thresholds related to mitigation of extreme flood impacts are well-understood and defined by organizational protocol, but others are difficult to quantify due to reliance on contextual expert knowledge, experience, and complexity of information necessary to make certain decisions. Our research attempts to address this issue by demonstrating participatory modeling methods designed to help flood managers (1) better understand and parameterize local decision thresholds in extreme flood management situations, (2) collectively learn about scaling management decision thresholds to future local flooding scenarios and (3) identify effective strategies for adaptating flood mitigation actions and organizational response to climate change-intensified flooding. Our agent-based system dynamic models rely on expert knowledge from local flood managers and sophisticated, climate change-informed hydrological models to simulate current and future flood scenarios. Local flood managers from interact with these models by receiving dynamic information and making management decisions as a flood scenario progresses, allowing parametrization of decision thresholds under different scenarios. Flooding impacts are calculated in each iteration as a means of discussing effectiveness of responses and prioritizing response alternatives. We discuss the findings of this participatory modeling and educational process from a case study of Boston, MA, and discuss transferability of these methods to other types

  17. A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

    ERIC Educational Resources Information Center

    Xiang, Lin

    2011-01-01

    This is a collective case study seeking to develop detailed descriptions of how programming an agent-based simulation influences a group of 8th grade students' model-based inquiry (MBI) by examining students' agent-based programmable modeling (ABPM) processes and the learning outcomes. The context of the present study was a biology unit on…

  18. A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

    ERIC Educational Resources Information Center

    Xiang, Lin

    2011-01-01

    This is a collective case study seeking to develop detailed descriptions of how programming an agent-based simulation influences a group of 8th grade students' model-based inquiry (MBI) by examining students' agent-based programmable modeling (ABPM) processes and the learning outcomes. The context of the present study was a biology unit on…

  19. Assortative Mating and the Reversal of Gender Inequality in Education in Europe: An Agent-Based Model

    PubMed Central

    Grow, André; Van Bavel, Jan

    2015-01-01

    While men have always received more education than women in the past, this gender imbalance in education has turned around in large parts of the world. In many countries, women now excel men in terms of participation and success in higher education. This implies that, for the first time in history, there are more highly educated women than men reaching the reproductive ages and looking for a partner. We develop an agent-based computational model that explicates the mechanisms that may have linked the reversal of gender inequality in education with observed changes in educational assortative mating. Our model builds on the notion that individuals search for spouses in a marriage market and evaluate potential candidates based on preferences. Based on insights from earlier research, we assume that men and women prefer partners with similar educational attainment and high earnings prospects, that women tend to prefer men who are somewhat older than themselves, and that men prefer women who are in their mid-twenties. We also incorporate the insight that the educational system structures meeting opportunities on the marriage market. We assess the explanatory power of our model with systematic computational experiments, in which we simulate marriage market dynamics in 12 European countries among individuals born between 1921 and 2012. In these experiments, we make use of realistic agent populations in terms of educational attainment and earnings prospects and validate model outcomes with data from the European Social Survey. We demonstrate that the observed changes in educational assortative mating can be explained without any change in male or female preferences. We argue that our model provides a useful computational laboratory to explore and quantify the implications of scenarios for the future. PMID:26039151

  20. Assortative mating and the reversal of gender inequality in education in europe: an agent-based model.

    PubMed

    Grow, André; Van Bavel, Jan

    2015-01-01

    While men have always received more education than women in the past, this gender imbalance in education has turned around in large parts of the world. In many countries, women now excel men in terms of participation and success in higher education. This implies that, for the first time in history, there are more highly educated women than men reaching the reproductive ages and looking for a partner. We develop an agent-based computational model that explicates the mechanisms that may have linked the reversal of gender inequality in education with observed changes in educational assortative mating. Our model builds on the notion that individuals search for spouses in a marriage market and evaluate potential candidates based on preferences. Based on insights from earlier research, we assume that men and women prefer partners with similar educational attainment and high earnings prospects, that women tend to prefer men who are somewhat older than themselves, and that men prefer women who are in their mid-twenties. We also incorporate the insight that the educational system structures meeting opportunities on the marriage market. We assess the explanatory power of our model with systematic computational experiments, in which we simulate marriage market dynamics in 12 European countries among individuals born between 1921 and 2012. In these experiments, we make use of realistic agent populations in terms of educational attainment and earnings prospects and validate model outcomes with data from the European Social Survey. We demonstrate that the observed changes in educational assortative mating can be explained without any change in male or female preferences. We argue that our model provides a useful computational laboratory to explore and quantify the implications of scenarios for the future.

  1. Agent Based Modeling of Air Carrier Behavior for Evaluation of Technology Equipage and Adoption

    NASA Technical Reports Server (NTRS)

    Horio, Brant M.; DeCicco, Anthony H.; Stouffer, Virginia L.; Hasan, Shahab; Rosenbaum, Rebecca L.; Smith, Jeremy C.

    2014-01-01

    As part of ongoing research, the National Aeronautics and Space Administration (NASA) and LMI developed a research framework to assist policymakers in identifying impacts on the U.S. air transportation system (ATS) of potential policies and technology related to the implementation of the Next Generation Air Transportation System (NextGen). This framework, called the Air Transportation System Evolutionary Simulation (ATS-EVOS), integrates multiple models into a single process flow to best simulate responses by U.S. commercial airlines and other ATS stakeholders to NextGen-related policies, and in turn, how those responses impact the ATS. Development of this framework required NASA and LMI to create an agent-based model of airline and passenger behavior. This Airline Evolutionary Simulation (AIRLINE-EVOS) models airline decisions about tactical airfare and schedule adjustments, and strategic decisions related to fleet assignments, market prices, and equipage. AIRLINE-EVOS models its own heterogeneous population of passenger agents that interact with airlines; this interaction allows the model to simulate the cycle of action-reaction as airlines compete with each other and engage passengers. We validated a baseline configuration of AIRLINE-EVOS against Airline Origin and Destination Survey (DB1B) data and subject matter expert opinion, and we verified the ATS-EVOS framework and agent behavior logic through scenario-based experiments. These experiments demonstrated AIRLINE-EVOS's capabilities in responding to an input price shock in fuel prices, and to equipage challenges in a series of analyses based on potential incentive policies for best equipped best served, optimal-wind routing, and traffic management initiative exemption concepts..

  2. Policies to Reduce Influenza in the Workplace: Impact Assessments Using an Agent-Based Model

    PubMed Central

    Grefenstette, John J.; Galloway, David; Albert, Steven M.; Burke, Donald S.

    2013-01-01

    Objectives. We examined the impact of access to paid sick days (PSDs) and stay-at-home behavior on the influenza attack rate in workplaces. Methods. We used an agent-based model of Allegheny County, Pennsylvania, with PSD data from the US Bureau of Labor Statistics, standard influenza epidemic parameters, and the probability of staying home when ill. We compared the influenza attack rate among employees resulting from workplace transmission, focusing on the effects of presenteeism (going to work when ill). Results. In a simulated influenza epidemic (R0 = 1.4), the attack rate among employees owing to workplace transmission was 11.54%. A large proportion (72.00%) of this attack rate resulted from exposure to employees engaging in presenteeism. Universal PSDs reduced workplace infections by 5.86%. Providing 1 or 2 “flu days”—allowing employees with influenza to stay home—reduced workplace infections by 25.33% and 39.22%, respectively. Conclusions. PSDs reduce influenza transmission owing to presenteeism and, hence, the burden of influenza illness in workplaces. PMID:23763426

  3. Agent-based modelling of mosquito foraging behaviour for malaria control.

    PubMed

    Gu, Weidong; Novak, Robert J

    2009-11-01

    Traditional environmental management programmes require extensive coverage of larval habitats to reduce drastically the emergence of adult mosquitoes. Recent studies have highlighted the impact of reduced availability of aquatic habitats on mosquito foraging for hosts and oviposition sites. In this study, we developed an agent-based model to track the status and movement of mosquitoes individually. Mosquito foraging was represented as a two-stage process: random flight when the resource was not within the mosquito's perception range and directional flight to the resource when it was detected. Three scenarios of targeted source reduction were devised to eliminate all aquatic habitats within certain distances of human habitations. For comparison, three non-targeted source reductions randomly eliminated the same numbers of aquatic habitats as their corresponding targeted scenarios. Our results show that the elimination of habitats within 100m, 200m and 300m of surrounding houses resulted in 13%, 91% and 94% reductions in malaria incidence, respectively; compared with -3%, 19% and 44%, respectively, for the corresponding conventional interventions. These findings indicate that source reduction might not require coverage of extensive areas, as previously thought, and that the distance to human habitations can be used for habitat targeting.

  4. Fortune Favours the Bold: An Agent-Based Model Reveals Adaptive Advantages of Overconfidence in War

    PubMed Central

    Johnson, Dominic D. P.; Weidmann, Nils B.; Cederman, Lars-Erik

    2011-01-01

    Overconfidence has long been considered a cause of war. Like other decision-making biases, overconfidence seems detrimental because it increases the frequency and costs of fighting. However, evolutionary biologists have proposed that overconfidence may also confer adaptive advantages: increasing ambition, resolve, persistence, bluffing opponents, and winning net payoffs from risky opportunities despite occasional failures. We report the results of an agent-based model of inter-state conflict, which allows us to evaluate the performance of different strategies in competition with each other. Counter-intuitively, we find that overconfident states predominate in the population at the expense of unbiased or underconfident states. Overconfident states win because: (1) they are more likely to accumulate resources from frequent attempts at conquest; (2) they are more likely to gang up on weak states, forcing victims to split their defences; and (3) when the decision threshold for attacking requires an overwhelming asymmetry of power, unbiased and underconfident states shirk many conflicts they are actually likely to win. These “adaptive advantages” of overconfidence may, via selection effects, learning, or evolved psychology, have spread and become entrenched among modern states, organizations and decision-makers. This would help to explain the frequent association of overconfidence and war, even if it no longer brings benefits today. PMID:21731627

  5. An Agent-Based Modeling Approach for Determining Corn Stover Removal Rate and Transboundary Effects

    NASA Astrophysics Data System (ADS)

    Gan, Jianbang; Langeveld, J. W. A.; Smith, C. T.

    2014-02-01

    Bioenergy production involves different agents with potentially different objectives, and an agent's decision often has transboundary impacts on other agents along the bioenergy value chain. Understanding and estimating the transboundary impacts is essential to portraying the interactions among the different agents and in the search for the optimal configuration of the bioenergy value chain. We develop an agent-based model to mimic the decision making by feedstock producers and feedstock-to-biofuel conversion plant operators and propose multipliers (i.e., ratios of economic values accruing to different segments and associated agents in the value chain) for assessing the transboundary impacts. Our approach is generic and thus applicable to a variety of bioenergy production systems at different sites and geographic scales. We apply it to the case of producing ethanol using corn stover in Iowa, USA. The results from the case study indicate that stover removal rate is site specific and varies considerably with soil type, as well as other factors, such as stover price and harvesting cost. In addition, ethanol production using corn stover in the study region would have strong positive ripple effects, with the values of multipliers varying with greenhouse gas price and national energy security premium. The relatively high multiplier values suggest that a large portion of the value associated with corn stover ethanol production would accrue to the downstream end of the value chain instead of stover producers.

  6. Fortune favours the bold: an agent-based model reveals adaptive advantages of overconfidence in war.

    PubMed

    Johnson, Dominic D P; Weidmann, Nils B; Cederman, Lars-Erik

    2011-01-01

    Overconfidence has long been considered a cause of war. Like other decision-making biases, overconfidence seems detrimental because it increases the frequency and costs of fighting. However, evolutionary biologists have proposed that overconfidence may also confer adaptive advantages: increasing ambition, resolve, persistence, bluffing opponents, and winning net payoffs from risky opportunities despite occasional failures. We report the results of an agent-based model of inter-state conflict, which allows us to evaluate the performance of different strategies in competition with each other. Counter-intuitively, we find that overconfident states predominate in the population at the expense of unbiased or underconfident states. Overconfident states win because: (1) they are more likely to accumulate resources from frequent attempts at conquest; (2) they are more likely to gang up on weak states, forcing victims to split their defences; and (3) when the decision threshold for attacking requires an overwhelming asymmetry of power, unbiased and underconfident states shirk many conflicts they are actually likely to win. These "adaptive advantages" of overconfidence may, via selection effects, learning, or evolved psychology, have spread and become entrenched among modern states, organizations and decision-makers. This would help to explain the frequent association of overconfidence and war, even if it no longer brings benefits today.

  7. An agent-based model of dune interactions produces the emergence of patterns in deserts

    NASA Astrophysics Data System (ADS)

    Génois, M.; Courrech Du Pont, S.

    2013-12-01

    Crescent-shaped barchan dunes are highly mobile dunes which are ubiquitous on Earth and other solar system bodies. Although they are unstable when considered separately, they form large assemblies in deserts and spatially organize in narrow corridors that extend in the wind direction. Collision of barchans has been proposed as a mechanism to redistribute sand between dunes and prevent the formation of very large dunes. Here, we use an agent-based model with elementary rules of sand redistribution during collisions to access the full dynamics of very large barchan fields. We tune the dune field density by changing the sand load/lost ratio and follow the transition between dilute fields, where barchans barely interact, and dense fields, where dune collisions control and stabilize the dune field. In this dense regime, barchans have a small, well selected size and form flocks: the dune field self-organizes in narrow corridors of dunes, as it is observed in real dense barchan deserts. Simulated dense barchan field, with spatial structuring along the wind direction.

  8. An agent-based model of dune interactions produces the emergence of patterns in deserts

    NASA Astrophysics Data System (ADS)

    GéNois, Mathieu; Pont, Sylvain Courrech; Hersen, Pascal; GréGoire, Guillaume

    2013-08-01

    Crescent-shaped barchan dunes are highly mobile dunes which are ubiquitous on Earth and other solar system bodies. Although they are unstable when considered separately, they form large assemblies in deserts and spatially organize in narrow corridors that extend in the wind direction. Collision of barchans has been proposed as a mechanism to redistribute sand between dunes and prevent the formation of very large dunes. Here we use an agent-based model with elementary rules of sand redistribution during collisions to access the full dynamics of very large barchan fields. We tune the dune field density by changing the sand load/lost ratio and follow the transition between dilute fields, where barchans barely interact, and dense fields, where dune collisions control and stabilize the dune field. In this dense regime, barchans have a small, well-selected size and form flocks: the dune field self-organizes in narrow corridors of dunes, as it is observed in real dense barchan deserts.

  9. Agent-based modeling of physical activity behavior and environmental correlations: an introduction and illustration.

    PubMed

    Zhu, Weimo; Nedovic-Budic, Zorica; Olshansky, Robert B; Marti, Jed; Gao, Yong; Park, Youngsik; McAuley, Edward; Chodzko-Zajko, Wojciech

    2013-03-01

    To introduce Agent-Based Model (ABM) to physical activity (PA) research and, using data from a study of neighborhood walkability and walking behavior, to illustrate parameters for an ABM of walking behavior. The concept, brief history, mechanism, major components, key steps, advantages, and limitations of ABM were first introduced. For illustration, 10 participants (age in years: mean = 68, SD = 8) were recruited from a walkable and a nonwalkable neighborhood. They wore AMP 331 triaxial accelerometers and GeoLogger GPA tracking devices for 21 days. Data were analyzed using conventional statistics and highresolution geographic image analysis, which focused on a) path length, b) path duration, c) number of GPS reporting points, and d) interaction between distances and time. Average steps by subjects ranged from 1810-10,453 steps per day (mean = 6899, SD = 3823). No statistical difference in walking behavior was found between neighborhoods (Walkable = 6710 ± 2781, Nonwalkable = 7096 ± 4674). Three environment parameters (ie, sidewalk, crosswalk, and path) were identified for future ABM simulation. ABM should provide a better understanding of PA behavior's interaction with the environment, as illustrated using a real-life example. PA field should take advantage of ABM in future research.

  10. Agent Based Modeling of Atherosclerosis: A Concrete Help in Personalized Treatments

    NASA Astrophysics Data System (ADS)

    Pappalardo, Francesco; Cincotti, Alessandro; Motta, Alfredo; Pennisi, Marzio

    Atherosclerosis, a pathology affecting arterial blood vessels, is one of most common diseases of the developed countries. We present studies on the increased atherosclerosis risk using an agent based model of atherogenesis that has been previously validated using clinical data. It is well known that the major risk in atherosclerosis is the persistent high level of low density lipoprotein (LDL) concentration. However, it is not known if short period of high LDL concentration can cause irreversible damage and if reduction of the LDL concentration (either by life style or drug) can drastically or partially reduce the already acquired risk. We simulated four different clinical situations in a large set of virtual patients (200 per clinical scenario). In the first one the patients lifestyle maintains the concentration of LDL in a no risk range. This is the control case simulation. The second case is represented by patients having high level of LDL with a delay to apply appropriate treatments; The third scenario is characterized by patients with high LDL levels treated with specific drugs like statins. Finally we simulated patients that are characterized by several oxidative events (smoke, sedentary life style, assumption of alcoholic drinks and so on so forth) that effective increase the risk of LDL oxidation. Those preliminary results obviously need to be clinically investigated. It is clear, however, that SimAthero has the power to concretely help medical doctors and clinicians in choosing personalized treatments for the prevention of the atherosclerosis damages.

  11. Agent-based modelling of mosquito foraging behaviour for malaria control

    PubMed Central

    Gu, Weidong; Novak, Robert J.

    2009-01-01

    Summary Traditional environmental management programmes require extensive coverage of larval habitats to reduce drastically the emergence of adult mosquitoes. Recent studies have highlighted the impact of reduced availability of aquatic habitats on mosquito foraging for hosts and oviposition sites. In this study, we developed an agent-based model to track the status and movement of mosquitoes individually. Mosquito foraging was represented as a two-stage process: random flight when the resource was not within the mosquito’s perception range and directional flight to the resource when it was detected. Three scenarios of targeted source reduction were devised to eliminate all aquatic habitats within certain distances of human habitations. For comparison, three conventional source reductions randomly eliminated the same numbers of aquatic habitats as their corresponding targeted scenarios. Our results show that the elimination of habitats within 100 m, 200 m and 300 m of surrounding houses resulted in 13%, 91% and 94% reductions in malaria incidence, respectively; compared with −3%, 19% and 44%, respectively, for the corresponding conventional interventions. These findings indicate that source reduction might not require coverage of extensive areas, as previously thought, and that the distance to human habitations can be used for habitat targeting. PMID:19200566

  12. An agent-based modeling approach for determining corn stover removal rate and transboundary effects.

    PubMed

    Gan, Jianbang; Langeveld, J W A; Smith, C T

    2014-02-01

    Bioenergy production involves different agents with potentially different objectives, and an agent's decision often has transboundary impacts on other agents along the bioenergy value chain. Understanding and estimating the transboundary impacts is essential to portraying the interactions among the different agents and in the search for the optimal configuration of the bioenergy value chain. We develop an agent-based model to mimic the decision making by feedstock producers and feedstock-to-biofuel conversion plant operators and propose multipliers (i.e., ratios of economic values accruing to different segments and associated agents in the value chain) for assessing the transboundary impacts. Our approach is generic and thus applicable to a variety of bioenergy production systems at different sites and geographic scales. We apply it to the case of producing ethanol using corn stover in Iowa, USA. The results from the case study indicate that stover removal rate is site specific and varies considerably with soil type, as well as other factors, such as stover price and harvesting cost. In addition, ethanol production using corn stover in the study region would have strong positive ripple effects, with the values of multipliers varying with greenhouse gas price and national energy security premium. The relatively high multiplier values suggest that a large portion of the value associated with corn stover ethanol production would accrue to the downstream end of the value chain instead of stover producers.

  13. Agent-based modeling approach of immune defense against spores of opportunistic human pathogenic fungi.

    PubMed

    Tokarski, Christian; Hummert, Sabine; Mech, Franziska; Figge, Marc Thilo; Germerodt, Sebastian; Schroeter, Anja; Schuster, Stefan

    2012-01-01

    Opportunistic human pathogenic fungi like the ubiquitous fungus Aspergillus fumigatus are a major threat to immunocompromised patients. An impaired immune system renders the body vulnerable to invasive mycoses that often lead to the death of the patient. While the number of immunocompromised patients is rising with medical progress, the process, and dynamics of defense against invaded and ready to germinate fungal conidia are still insufficiently understood. Besides macrophages, neutrophil granulocytes form an important line of defense in that they clear conidia. Live imaging shows the interaction of those phagocytes and conidia as a dynamic process of touching, dragging, and phagocytosis. To unravel strategies of phagocytes on the hunt for conidia an agent-based modeling approach is used, implemented in NetLogo. Different modes of movement of phagocytes are tested regarding their clearing efficiency: random walk, short-term persistence in their recent direction, chemotaxis of chemokines excreted by conidia, and communication between phagocytes. While the short-term persistence hunting strategy turned out to be superior to the simple random walk, following a gradient of chemokines released by conidial agents is even better. The advantage of communication between neutrophilic agents showed a strong dependency on the spatial scale of the focused area and the distribution of the pathogens.

  14. Evaluating Infection Prevention Strategies in Out-Patient Dialysis Units Using Agent-Based Modeling.

    PubMed

    Wares, Joanna R; Lawson, Barry; Shemin, Douglas; D'Agata, Erika M C

    2016-01-01

    Patients receiving chronic hemodialysis (CHD) are among the most vulnerable to infections caused by multidrug-resistant organisms (MDRO), which are associated with high rates of morbidity and mortality. Current guidelines to reduce transmission of MDRO in the out-patient dialysis unit are targeted at patients considered to be high-risk for transmitting these organisms: those with infected skin wounds not contained by a dressing, or those with fecal incontinence or uncontrolled diarrhea. Here, we hypothesize that targeting patients receiving antimicrobial treatment would more effectively reduce transmission and acquisition of MDRO. We also hypothesize that environmental contamination plays a role in the dissemination of MDRO in the dialysis unit. To address our hypotheses, we built an agent-based model to simulate different treatment strategies in a dialysis unit. Our results suggest that reducing antimicrobial treatment, either by reducing the number of patients receiving treatment or by reducing the duration of the treatment, markedly reduces overall colonization rates and also the levels of environmental contamination in the dialysis unit. Our results also suggest that improving the environmental decontamination efficacy between patient dialysis treatments is an effective method for reducing colonization and contamination rates. These findings have important implications for the development and implementation of future infection prevention strategies.

  15. Optimization of HAART with genetic algorithms and agent-based models of HIV infection.

    PubMed

    Castiglione, F; Pappalardo, F; Bernaschi, M; Motta, S

    2007-12-15

    Highly Active AntiRetroviral Therapies (HAART) can prolong life significantly to people infected by HIV since, although unable to eradicate the virus, they are quite effective in maintaining control of the infection. However, since HAART have several undesirable side effects, it is considered useful to suspend the therapy according to a suitable schedule of Structured Therapeutic Interruptions (STI). In the present article we describe an application of genetic algorithms (GA) aimed at finding the optimal schedule for a HAART simulated with an agent-based model (ABM) of the immune system that reproduces the most significant features of the response of an organism to the HIV-1 infection. The genetic algorithm helps in finding an optimal therapeutic schedule that maximizes immune restoration, minimizes the viral count and, through appropriate interruptions of the therapy, minimizes the dose of drug administered to the simulated patient. To validate the efficacy of the therapy that the genetic algorithm indicates as optimal, we ran simulations of opportunistic diseases and found that the selected therapy shows the best survival curve among the different simulated control groups. A version of the C-ImmSim simulator is available at http://www.iac.cnr.it/~filippo/c-ImmSim.html

  16. Vascular Adaptation: Pattern Formation and Cross Validation between an Agent Based Model and a Dynamical System.

    PubMed

    Garbey, Marc; Casarin, Stefano; Berceli, Scott A

    2017-09-21

    Myocardial infarction is the global leading cause of mortality (Go et al., 2014). Coronary artery occlusion is its main etiology and it is commonly treated by Coronary Artery Bypass Graft (CABG) surgery (Wilson et al, 2007). The long-term outcome remains unsatisfactory (Benedetto, 2016) as the graft faces the phenomenon of restenosis during the post-surgery, which consists of re-occlusion of the lumen and usually requires secondary intervention even within one year after the initial surgery (Harskamp, 2013). In this work, we propose an extensive study of the restenosis phenomenon by implementing two mathematical models previously developed by our group: a heuristic Dynamical System (DS) (Garbey and Berceli, 2013), and a stochastic Agent Based Model (ABM) (Garbey et al., 2015). With an extensive use of the ABM, we retrieved the pattern formations of the cellular events that mainly lead the restenosis, especially focusing on mitosis in intima, caused by alteration in shear stress, and mitosis in media, fostered by alteration in wall tension. A deep understanding of the elements at the base of the restenosis is indeed crucial in order to improve the final outcome of vein graft bypass. We also turned the ABM closer to the physiological reality by abating its original assumption of circumferential symmetry. This allowed us to finely replicate the trigger event of the restenosis, i.e. the loss of the endothelium in the early stage of the post-surgical follow up (Roubos et al., 1995) and to simulate the encroachment of the lumen in a fashion aligned with histological evidences (Owens et al., 2015). Finally, we cross-validated the two models by creating an accurate matching procedure. In this way we added the degree of accuracy given by the ABM to a simplified model (DS) that can serve as powerful predictive tool for the clinic. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity

    PubMed Central

    Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

    2017-01-01

    Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying

  18. An Agent-Based Discrete Collagen Fiber Network Model of Dynamic Traction Force-Induced Remodeling.

    PubMed

    Reinhardt, James W; Gooch, Keith

    2017-09-21

    We developed an agent-based model that incorporates repetitively applied traction force within a discrete fiber network to understand how microstructural properties of the network influence mechanical properties and traction force-induced remodeling. An important difference between our model and similar finite-element models is that by implementing more biologically-realistic dynamic traction, we can explore a greater range of matrix remodeling. Here, we validated our model by reproducing qualitative trends observed in three sets of experimental data reported by others: tensile and shear testing of cell-free collagen gels, collagen remodeling around a single isolated cell, and collagen remodeling between pairs of cells. In response to tensile and shear strain, simulated acellular networks exhibited biphasic stress-strain curves indicative of strain-stiffening. Our data support the notion that strain-stiffening might occur as individual fibrils successively align along the axis of strain and become engaged in tension. In simulations with a single, contractile cell, peak collagen displacement occurred closest to the cell and decreased with increasing distance. In simulations with two cells, compaction of collagen between cells appeared inversely related to the initial distance between cells. Further analysis revealed strain energy was relatively uniform around the outer surface of cells separated by 250 microns, but became increasingly non-uniform as the distance between cells decreased. This pattern was partly attributable to the pattern of collagen compaction. These findings are of interest because fibril alignment, density, and strain energy may each contribute to contact guidance during tissue morphogenesis.

  19. An Agent-based Simulation Model for C. difficile Infection Control

    PubMed Central

    Codella, James; Safdar, Nasia; Heffernan, Rick; Alagoz, Oguzhan

    2014-01-01

    Background. Control of C. difficile infection (CDI) is an increasingly difficult problem for healthcare institutions. There are commonly recommended strategies to combat CDI transmission such as oral vancomycin for CDI treatment, increased hand hygiene with soap and water for healthcare workers, daily environmental disinfection of infected patient rooms, and contact isolation of diseased patients. However, the efficacy of these strategies, particularly for endemic CDI, has not been well studied. The objective of this research is to develop a valid agent-based simulation model (ABM) to study C. difficile transmission and control in a mid-sized hospital. Methods. We develop an ABM of a mid-sized hospital with agents such as patients, healthcare workers, and visitors. We model the natural progression of CDI in a patient using a Markov chain and the transmission of CDI through agent and environmental interactions. We derive input parameters from aggregate patient data from the 2007-2010 Wisconsin Hospital Association and published medical literature. We define a calibration process, which we use to estimate transition probabilities of the Markov model by comparing simulation results to benchmark values found in published literature. Results. Comparing CDI control strategies implemented individually, routine bleach disinfection of CDI+ patient rooms provides the largest reduction in nosocomial asymptomatic colonizations (21.8%) and nosocomial CDIs (42.8%). Additionally, vancomycin treatment provides the largest reduction in relapse CDIs (41.9%), CDI-related mortalities (68.5%), and total patient LOS (21.6%). Conclusion. We develop a generalized ABM for CDI control that can be customized and further expanded to specific institutions and/or scenarios. Additionally, we estimate transition probabilities for a Markov model of natural CDI progression in a patient through calibration. PMID:25112595

  20. Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity.

    PubMed

    Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

    2017-01-01

    Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying

  1. Independence and interdependence in the nest-site choice by honeybee swarms: Agent-based models, analytical approaches and pattern formation.

    PubMed

    Galla, Tobias

    2010-01-07

    In a recent paper List, Elsholtz and Seeley (List et al., 2009) have devised an agent-based model of the nest-choice dynamics in swarms of honeybees, and have concluded that both interdependence and independence are needed for the bees to reach a consensus on the best nest site. We here present a simplified version of the model which can be treated analytically with the tools of statistical physics and which largely has the same features as the original dynamics. Based on our analytical approaches it is possible to characterize the co-ordination outcome exactly on the deterministic level, and to a good approximation if stochastic effects are taken into account, reducing the need for computer simulations on the agent-based level. In the second part of the paper we present a spatial extension, and show that transient non-trivial patterns emerge, before consensus is reached. Approaches in terms of Langevin equations for continuous field variables are discussed.

  2. A risk assessment example for soil invertebrates using spatially explicit agent-based models.

    PubMed

    Reed, Melissa; Alvarez, Tania; Chelinho, Sónia; Forbes, Valery; Johnston, Alice; Meli, Mattia; Voss, Frank; Pastorok, Rob

    2016-01-01

    Current risk assessment methods for measuring the toxicity of plant protection products (PPPs) on soil invertebrates use standardized laboratory conditions to determine acute effects on mortality and sublethal effects on reproduction. If an unacceptable risk is identified at the lower tier, population-level effects are assessed using semifield and field trials at a higher tier because modeling methods for extrapolating available lower-tier information to population effects have not yet been implemented. Field trials are expensive, time consuming, and cannot be applied to variable landscape scenarios. Mechanistic modeling of the toxicological effects of PPPs on individuals and their responses combined with simulation of population-level response shows great potential in fulfilling such a need, aiding ecologically informed extrapolation. Here, we introduce and demonstrate the potential of 2 population models for ubiquitous soil invertebrates (collembolans and earthworms) as refinement options in current risk assessment. Both are spatially explicit agent-based models (ABMs), incorporating individual and landscape variability. The models were used to provide refined risk assessments for different application scenarios of a hypothetical pesticide applied to potato crops (full-field spray onto the soil surface [termed "overall"], in-furrow, and soil-incorporated pesticide applications). In the refined risk assessment, the population models suggest that soil invertebrate populations would likely recover within 1 year after pesticide application, regardless of application method. The population modeling for both soil organisms also illustrated that a lower predicted average environmental concentration in soil (PECsoil) could potentially lead to greater effects at the population level, depending on the spatial heterogeneity of the pesticide and the behavior of the soil organisms. Population-level effects of spatial-temporal variations in exposure were elucidated in the

  3. Agent-based modeling of oxygen-responsive transcription factors in Escherichia coli.

    PubMed

    Bai, Hao; Rolfe, Matthew D; Jia, Wenjing; Coakley, Simon; Poole, Robert K; Green, Jeffrey; Holcombe, Mike

    2014-04-01

    In the presence of oxygen (O2) the model bacterium Escherichia coli is able to conserve energy by aerobic respiration. Two major terminal oxidases are involved in this process - Cyo has a relatively low affinity for O2 but is able to pump protons and hence is energetically efficient; Cyd has a high affinity for O2 but does not pump protons. When E. coli encounters environments with different O2 availabilities, the expression of the genes encoding the alternative terminal oxidases, the cydAB and cyoABCDE operons, are regulated by two O2-responsive transcription factors, ArcA (an indirect O2 sensor) and FNR (a direct O2 sensor). It has been suggested that O2-consumption by the terminal oxidases located at the cytoplasmic membrane significantly affects the activities of ArcA and FNR in the bacterial nucleoid. In this study, an agent-based modeling approach has been taken to spatially simulate the uptake and consumption of O2 by E. coli and the consequent modulation of ArcA and FNR activities based on experimental data obtained from highly controlled chemostat cultures. The molecules of O2, transcription factors and terminal oxidases are treated as individual agents and their behaviors and interactions are imitated in a simulated 3-D E. coli cell. The model implies that there are two barriers that dampen the response of FNR to O2, i.e. consumption of O2 at the membrane by the terminal oxidases and reaction of O2 with cytoplasmic FNR. Analysis of FNR variants suggested that the monomer-dimer transition is the key step in FNR-mediated repression of gene expression.

  4. Real-Time Agent-Based Modeling Simulation with in-situ Visualization of Complex Biological Systems

    PubMed Central

    Seekhao, Nuttiiya; Shung, Caroline; JaJa, Joseph; Mongeau, Luc; Li-Jessen, Nicole Y. K.

    2016-01-01

    We present an efficient and scalable scheme for implementing agent-based modeling (ABM) simulation with In Situ visualization of large complex systems on heterogeneous computing platforms. The scheme is designed to make optimal use of the resources available on a heterogeneous platform consisting of a multicore CPU and a GPU, resulting in minimal to no resource idle time. Furthermore, the scheme was implemented under a client-server paradigm that enables remote users to visualize and analyze simulation data as it is being generated at each time step of the model. Performance of a simulation case study of vocal fold inflammation and wound healing with 3.8 million agents shows 35× and 7× speedup in execution time over single-core and multi-core CPU respectively. Each iteration of the model took less than 200 ms to simulate, visualize and send the results to the client. This enables users to monitor the simulation in real-time and modify its course as needed. PMID:27547508

  5. Designing an Agent-Based Model for Childhood Obesity Interventions: A Case Study of ChildObesity180.

    PubMed

    Hennessy, Erin; Ornstein, Joseph T; Economos, Christina D; Herzog, Julia Bloom; Lynskey, Vanessa; Coffield, Edward; Hammond, Ross A

    2016-01-07

    Complex systems modeling can provide useful insights when designing and anticipating the impact of public health interventions. We developed an agent-based, or individual-based, computation model (ABM) to aid in evaluating and refining implementation of behavior change interventions designed to increase physical activity and healthy eating and reduce unnecessary weight gain among school-aged children. The potential benefits of applying an ABM approach include estimating outcomes despite data gaps, anticipating impact among different populations or scenarios, and exploring how to expand or modify an intervention. The practical challenges inherent in implementing such an approach include data resources, data availability, and the skills and knowledge of ABM among the public health obesity intervention community. The aim of this article was to provide a step-by-step guide on how to develop an ABM to evaluate multifaceted interventions on childhood obesity prevention in multiple settings. We used data from 2 obesity prevention initiatives and public-use resources. The details and goals of the interventions, overview of the model design process, and generalizability of this approach for future interventions is discussed.

  6. Using an agent-based model to examine forest management outcomes in a fire-prone landscape in Oregon, USA

    Treesearch

    Thomas A. Spies; Eric White; Alan Ager; Jeffrey D. Kline; John P. Bolte; Emily K. Platt; Keith A. Olsen; Robert J. Pabst; Ana M. G. Barros; John D. Bailey; Susan Charnley; Anita T. Morzillo; Jennifer Koch; Michelle M. Steen-Adams; Peter H. Singleton; James Sulzman; Cynthia Schwartz; Blair Csuti

    2017-01-01

    Fire-prone landscapes present many challenges for both managers and policy makers in developing adaptive behaviors and institutions. We used a coupled human and natural systems framework and an agent-based landscape model to examine how alternative management scenarios affect fire and ecosystem services metrics in a fire-prone multiownership landscape in the eastern...

  7. An agent-based model for mRNA export through the nuclear pore complex.

    PubMed

    Azimi, Mohammad; Bulat, Evgeny; Weis, Karsten; Mofrad, Mohammad R K

    2014-11-05

    mRNA export from the nucleus is an essential step in the expression of every protein- coding gene in eukaryotes, but many aspects of this process remain poorly understood. The density of export receptors that must bind an mRNA to ensure export, as well as how receptor distribution affects transport dynamics, is not known. It is also unclear whether the rate-limiting step for transport occurs at the nuclear basket, in the central channel, or on the cytoplasmic face of the nuclear pore complex. Using previously published biophysical and biochemical parameters of mRNA export, we implemented a three-dimensional, coarse-grained, agent-based model of mRNA export in the nanosecond regime to gain insight into these issues. On running the model, we observed that mRNA export is sensitive to the number and distribution of transport receptors coating the mRNA and that there is a rate-limiting step in the nuclear basket that is potentially associated with the mRNA reconfiguring itself to thread into the central channel. Of note, our results also suggest that using a single location-monitoring mRNA label may be insufficient to correctly capture the time regime of mRNA threading through the pore and subsequent transport. This has implications for future experimental design to study mRNA transport dynamics. © 2014 Azimi, Bulat, et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  8. Diffusion of a Sustainable Farming Technique in Sri Lanka: An Agent-Based Modeling Approach

    NASA Astrophysics Data System (ADS)

    Jacobi, J. H.; Gilligan, J. M.; Carrico, A. R.; Truelove, H. B.; Hornberger, G.

    2012-12-01

    We live in a changing world - anthropogenic climate change is disrupting historic climate patterns and social structures are shifting as large scale population growth and massive migrations place unprecedented strain on natural and social resources. Agriculture in many countries is affected by these changes in the social and natural environments. In Sri Lanka, rice farmers in the Mahaweli River watershed have seen increases in temperature and decreases in precipitation. In addition, a government led resettlement project has altered the demographics and social practices in villages throughout the watershed. These changes have the potential to impact rice yields in a country where self-sufficiency in rice production is a point of national pride. Studies of the climate can elucidate physical effects on rice production, while research on social behaviors can illuminate the influence of community dynamics on agricultural practices. Only an integrated approach, however, can capture the combined and interactive impacts of these global changes on Sri Lankan agricultural. As part of an interdisciplinary team, we present an agent-based modeling (ABM) approach to studying the effects of physical and social changes on farmers in Sri Lanka. In our research, the diffusion of a sustainable farming technique, the system of rice intensification (SRI), throughout a farming community is modeled to identify factors that either inhibit or promote the spread of a more sustainable approach to rice farming. Inputs into the ABM are both physical and social and include temperature, precipitation, the Palmer Drought Severity Index (PDSI), community trust, and social networks. Outputs from the ABM demonstrate the importance of meteorology and social structure on the diffusion of SRI throughout a farming community.

  9. Reducing Income Inequalities in Food Consumption: Explorations With an Agent-Based Model.

    PubMed

    Blok, David J; de Vlas, Sake J; Bakker, Roel; van Lenthe, Frank J

    2015-10-01

    Individual and environmental factors dynamically interact in shaping income inequalities in healthy food consumption. The agent-based model, Health Behaviors Simulation (HEBSIM), was developed to describe income inequalities in healthy food consumption. It simulates interactions between households and their environment. HEBSIM was used to explore the impact of interventions aimed at reducing food consumption inequalities. HEBSIM includes households and food outlets. Households are characterized by location, composition, income, and preference for food. Decisions about where to shop for food (fruit/vegetable stores, supermarkets, or discount supermarkets) and whether to visit fast food outlets are based on distance, price, and food preference. Food outlets can close and new food outlets can enter the system. Three interventions to reduce healthy food consumption inequalities were tested: (1) eliminating residential segregation; (2) lowering the prices of healthy food; and (3) providing health education. HEBSIM was quantified using data from Statistics Netherlands, Statistics Eindhoven, and the GLOBE study (2011). The model mimicked food consumption in Eindhoven. High-income households visited healthy food shops more often than low-income households. Eliminating residential segregation had the largest impact in reducing income inequalities in food consumption, but resulted partly from a worsening in healthy food consumption in high-income households. Lowering prices and health education could also substantially reduce inequalities. Most interventions took 5-10 years to reach their (almost) full effects. HEBSIM is a promising tool for studying dynamic interactions between households and their environment and for assessing the impact of interventions on income inequalities in food consumption. Copyright © 2015 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

  10. The role of chromosome missegregation in cancer development: a theoretical approach using agent-based modelling.

    PubMed

    Araujo, Arturo; Baum, Buzz; Bentley, Peter

    2013-01-01

    Many cancers are aneuploid. However, the precise role that chromosomal instability plays in the development of cancer and in the response of tumours to treatment is still hotly debated. Here, to explore this question from a theoretical standpoint we have developed an agent-based model of tissue homeostasis in which to test the likely effects of whole chromosome mis-segregation during cancer development. In stochastic simulations, chromosome mis-segregation events at cell division lead to the generation of a diverse population of aneuploid clones that over time exhibit hyperplastic growth. Significantly, the course of cancer evolution depends on genetic linkage, as the structure of chromosomes lost or gained through mis-segregation events and the level of genetic instability function in tandem to determine the trajectory of cancer evolution. As a result, simulated cancers differ in their level of genetic stability and in their growth rates. We used this system to investigate the consequences of these differences in tumour heterogeneity for anti-cancer therapies based on surgery and anti-mitotic drugs that selectively target proliferating cells. As expected, simulated treatments induce a transient delay in tumour growth, and reveal a significant difference in the efficacy of different therapy regimes in treating genetically stable and unstable tumours. These data support clinical observations in which a poor prognosis is correlated with a high level of chromosome mis-segregation. However, stochastic simulations run in parallel also exhibit a wide range of behaviours, and the response of individual simulations (equivalent to single tumours) to anti-cancer therapy prove extremely variable. The model therefore highlights the difficulties of predicting the outcome of a given anti-cancer treatment, even in cases in which it is possible to determine the genotype of the entire set of cells within the developing tumour.

  11. Agent Based Modeling of “Crowdinforming” as a Means of Load Balancing at Emergency Departments

    PubMed Central

    Neighbour, Ryan; Oppenheimer, Luis; Mukhi, Shamir N.; Friesen, Marcia R.; McLeod, Robert D.

    2010-01-01

    This work extends ongoing development of a framework for modeling the spread of contact-transmission infectious diseases. The framework is built upon Agent Based Modeling (ABM), with emphasis on urban scale modelling integrated with institutional models of hospital emergency departments. The method presented here includes ABM modeling an outbreak of influenza-like illness (ILI) with concomitant surges at hospital emergency departments, and illustrates the preliminary modeling of ‘crowdinforming’ as an intervention. ‘Crowdinforming’, a component of ‘crowdsourcing’, is characterized as the dissemination of collected and processed information back to the ‘crowd’ via public access. The objective of the simulation is to allow for effective policy evaluation to better inform the public of expected wait times as part of their decision making process in attending an emergency department or clinic. In effect, this is a means of providing additional decision support garnered from a simulation, prior to real world implementation. The conjecture is that more optimal service delivery can be achieved under balanced patient loads, compared to situations where some emergency departments are overextended while others are underutilized. Load balancing optimization is a common notion in many operations, and the simulation illustrates that ‘crowdinforming’ is a potential tool when used as a process control parameter to balance the load at emergency departments as well as serving as an effective means to direct patients during an ILI outbreak with temporary clinics deployed. The information provided in the ‘crowdinforming’ model is readily available in a local context, although it requires thoughtful consideration in its interpretation. The extension to a wider dissemination of information via a web service is readily achievable and presents no technical obstacles, although political obstacles may be present. The ‘crowdinforming’ simulation is not limited to

  12. Bayesian networks and agent-based modeling approach for urban land-use and population density change: a BNAS model

    NASA Astrophysics Data System (ADS)

    Kocabas, Verda; Dragicevic, Suzana

    2013-10-01

    Land-use change models grounded in complexity theory such as agent-based models (ABMs) are increasingly being used to examine evolving urban systems. The objective of this study is to develop a spatial model that simulates land-use change under the influence of human land-use choice behavior. This is achieved by integrating the key physical and social drivers of land-use change using Bayesian networks (BNs) coupled with agent-based modeling. The BNAS model, integrated Bayesian network-based agent system, presented in this study uses geographic information systems, ABMs, BNs, and influence diagram principles to model population change on an irregular spatial structure. The model is parameterized with historical data and then used to simulate 20 years of future population and land-use change for the City of Surrey, British Columbia, Canada. The simulation results identify feasible new urban areas for development around the main transportation corridors. The obtained new development areas and the projected population trajectories with the“what-if” scenario capabilities can provide insights into urban planners for better and more informed land-use policy or decision-making processes.

  13. Fast revelation of the motif mode for a yeast protein interaction network through intelligent agent-based distributed computing.

    PubMed

    Lee, Wei-Po; Tzou, Wen-Shyong

    2010-09-01

    In the yeast protein-protein interaction network, motif mode, a collection of motifs of special combinations of protein nodes annotated by the molecular function terms of the Gene Ontology, has revealed differences in the conservation constraints within the same topology. In this study, by employing an intelligent agent-based distributed computing method, we are able to discover motif modes in a fast and adaptive manner. Moreover, by focusing on the highly evolutionarily conserved motif modes belonging to the same biological function, we find a large downshift in the distance between nodes belonging to the same motif mode compared with the whole, suggesting that nodes with the same motif mode tend to congregate in a network. Several motif modes with a high conservation of the motif constituents were revealed, but from a new perspective, including that with a three-node motif mode engaged in the protein fate and that with three four-node motif modes involved in the genome maintenance, cellular organization, and transcription. The network motif modes discovered from this method can be linked to the wealth of biological data which require further elucidation with regard to biological functions.

  14. A systems approach to healthcare: agent-based modeling, community mental health, and population well-being.

    PubMed

    Silverman, Barry G; Hanrahan, Nancy; Bharathy, Gnana; Gordon, Kim; Johnson, Dan

    2015-02-01

    Explore whether agent-based modeling and simulation can help healthcare administrators discover interventions that increase population wellness and quality of care while, simultaneously, decreasing costs. Since important dynamics often lie in the social determinants outside the health facilities that provide services, this study thus models the problem at three levels (individuals, organizations, and society). The study explores the utility of translating an existing (prize winning) software for modeling complex societal systems and agent's daily life activities (like a Sim City style of software), into a desired decision support system. A case study tests if the 3 levels of system modeling approach is feasible, valid, and useful. The case study involves an urban population with serious mental health and Philadelphia's Medicaid population (n=527,056), in particular. Section 3 explains the models using data from the case study and thereby establishes feasibility of the approach for modeling a real system. The models were trained and tuned using national epidemiologic datasets and various domain expert inputs. To avoid co-mingling of training and testing data, the simulations were then run and compared (Section 4.1) to an analysis of 250,000 Philadelphia patient hospital admissions for the year 2010 in terms of re-hospitalization rate, number of doctor visits, and days in hospital. Based on the Student t-test, deviations between simulated vs. real world outcomes are not statistically significant. Validity is thus established for the 2008-2010 timeframe. We computed models of various types of interventions that were ineffective as well as 4 categories of interventions (e.g., reduced per-nurse caseload, increased check-ins and stays, etc.) that result in improvement in well-being and cost. The 3 level approach appears to be useful to help health administrators sort through system complexities to find effective interventions at lower costs. Copyright © 2014 Elsevier B

  15. An agent-based model for water management and planning in the Lake Naivasha basin, Kenya

    NASA Astrophysics Data System (ADS)

    van Oel, Pieter; Mulatu, Dawit; Odongo, Vincent; Onyando, Japheth; Becht, Robert; van der Veen, Anne

    2013-04-01

    A variety of human and natural processes influence the ecological and economic state of the Lake Naivasha basin. The ecological wealth and recent economic developments in the area are strongly connected to Lake Naivasha which supports a rich variety of flora, mammal and bird species. Many human activities depend on clean freshwater from the lake whereas recently the freshwater availability of good quality is seriously influenced by water abstractions and the use of fertilizers in agriculture. Management alternatives include those aiming at limiting water abstractions and fertilizer use. A possible way to achieve reduced use of water and fertilizers is the introduction of Payment for Environmental Services (PES) schemes. As the Lake Naivasha basin and its population have experienced increasing pressures various disputes and disagreements have arisen about the processes responsible for the problems experienced, and the effectively of management alternatives. Beside conflicts of interest and disagreements on responsibilities there are serious factual disagreements. To share scientific knowledge on the effects of the socio-ecological system processes on the Lake Naivasha basin, tools may be used that expose information at temporal and spatial scales that are meaningful to stakeholders. In this study we use a spatially-explicit agent-based modelling (ABM) approach to depict the interactions between socio-economic and natural subsystems for supporting a more sustainable governance of the river basin resources. Agents consider alternative livelihood strategies and decide to go for the one they perceive as likely to be most profitable. Agents may predict and sense the availability of resources and also can observe economic performance achieved by neighbouring agents. Results are presented at the basin and subbasin level to provide relevant knowledge to Water Resources Users Associations which are important collective forums for water management through which PES schemes

  16. An agent-based model for the transmission dynamics of Toxoplasma gondii.

    PubMed

    Jiang, Wen; Sullivan, Adam M; Su, Chunlei; Zhao, Xiaopeng

    2012-01-21

    Toxoplasma gondii (T. gondii) is a unicellular protozoan that infects up to one-third of the world's human population. Numerous studies revealed that a latent infection of T. gondii can cause life-threatening encephalitis in immunocompromised people and also has significant effects on the behavior of healthy people and animals. However, the overall transmission of T. gondii has not been well understood although many factors affecting this process have been found out by different biologists separately. Here we synthesize what is currently known about the natural history of T. gondii by developing a prototype agent-based model to mimic the transmission process of T. gondii in a farm system. The present model takes into account the complete life cycle of T. gondii, which includes the transitions of the parasite from cats to environment through feces, from contaminated environment to mice through oocysts, from mice to cats through tissue cysts, from environment to cats through oocysts as well as the vertical transmission among mice. Although the current model does not explicitly include humans and other end-receivers, the effect of the transition to end-receivers is estimated by a developed infection risk index. The current model can also be extended to include human activities and thus be used to investigate the influences of human management on disease control. Simulation results reveal that most cats are infected through preying on infected mice while mice are infected through vertical transmission more often than through infection with oocysts, which clearly suggests the important role of mice during the transmission of T. gondii. Furthermore, our simulation results show that decreasing the number of mice on a farm can lead to the eradication of the disease and thus can lower the infection risk of other intermediate hosts on the farm. In addition, with the assumption that the relation between virulence and transmission satisfies a normal function, we show that

  17. An Agent-Based Modeling Approach to Integrate Tsunami Science, Human Behavior, and Unplanned Network Disruptions for Nearfield Tsunami Evacuation

    NASA Astrophysics Data System (ADS)

    Cox, D. T.; Wang, H.; Cramer, L.; Mostafizi, A.; Park, H.

    2016-12-01

    For the Cascadia Subduction Zone (CSZ) and other extreme near-field tsunami hazards, coastal residents and tourist must evacuate within 15 to 30 minutes immediately following intense ground-shaking and will be confronted with an array of choices: Should I evacuate on foot or by car? Alone, or find friends and family first? Head for high ground far away, or seek shelter a nearby building? How will the roads and bridges be affected by the preceding earthquake? In this project, we integrate the disciplines of tsunami inundation science, sociology, and civil engineering to investigate how decision-making by individual evacuees with respect to milling time, mode choice, and destination affects their life safety. We use an Agent-Based Model (ABM) to create credible scenarios for near-field tsunami evacuation. The ABM integrates (1) the time-dependent tsunami inundation computed separately using NOAA's ComMIT/MOST model, (2) population layers to account for variations in population density of residents and tourist, (3) evacuation route network including roads, bridges and foot paths for multi-modal transportation, and (4) evacuation destinations for horizontal and vertical evacuation. For this project, we apply the ABM at two locations: the city Seaside, OR, and South Beach State Park in Newport, OR. In the Seaside scenario, we show how unplanned network disruption - e.g. the partial or total failure of bridges due to the preceding earthquake - will affect life safety and show how the ABM can be used to provide retrofit strategies. For South Beach, we show how alternative routing can have a substantial impact on life safety. The ABM shows results that are initially counterintuitive. For the Seaside example, resource allocation for bridge retrofit favors investments in nodes and links not necessarily in close proximity to population centers. For the South Beach example, the routes which provide for the lowest risk (maximum life safety) are not always those with the

  18. Agent-based modeling for the landuse change of hunter-gather societies and the impacts on biodiversity in Guyana

    NASA Astrophysics Data System (ADS)

    Iwamura, T.; Fragoso, J.; Lambin, E.

    2012-12-01

    The interactions with animals are vital to the Amerindian, indigenous people, of Rupunini savannah-forest in Guyana. Their connections extend from basic energy and protein resource to spiritual bonding through "paring" to a certain animal in the forest. We collected extensive dataset of 23 indigenous communities for 3.5 years, consisting 9900 individuals from 1307 households, as well as animal observation data in 8 transects per communities (47,000 data entries). In this presentation, our research interest is to model the driver of land use change of the indigenous communities and its impacts on the ecosystem in the Rupunini area under global change. Overarching question we would like to answer with this program is to find how and why "tipping-point" from hunting gathering society to the agricultural society occurs in the future. Secondary question is what is the implication of the change to agricultural society in terms of biodiversity and carbon stock in the area, and eventually the well-being of Rupunini people. To answer the questions regarding the society shift in agriculture activities, we built as simulation with Agent-Based Modeling (Multi Agents Simulation). We developed this simulation by using Netlogo, the programming environment specialized for spatially explicit agent-based modeling (ABM). This simulation consists of four different process in the Rupunini landscape; forest succession, animal population growth, hunting of animals, and land clearing for agriculture. All of these processes are carried out by a set of computational unit, called "agents". In this program, there are four types of agents - patches, villages, households, and animals. Here, we describe the impacts of hunting on the biodiversity based on actual demographic data from one village named Crush Water. Animal population within the hunting territory of the village stabilized but Agouti/Paca dominates the landscape with little population of armadillos and peccaries. White-tailed deers

  19. Toward an Agent-Based Model of Socially Optimal Water Rights Markets

    NASA Astrophysics Data System (ADS)

    Ehlen, M. A.

    2004-12-01

    There has been considerable interest lately in using public markets for buying and selling the rights to local water usage. Such water rights markets, if designed correctly, should be socially optimal, that is, should sell rights at prices that reflect the true value of water in the region, taking into account that water rights buyers and sellers represent a disparate group of private industry, public authorities, and private users, each having different water needs and different priority to local government. Good market design, however, is hard. As was experienced in California short-run electric power markets, a market design that on paper looks reasonable but in practice is mal-constructed can have devastating effects: firms can learn to manipulate prices by `playing' both sides of the market, and sellers can under-provide so as to create exorbitant prices which buyers have no choice but to pay. Economic theory provides several frameworks for developing a good water rights market design; for example, the structure-conduct-performance paradigm (SCPP) suggests that, among other things, the number and types of buyers and sellers (structure), and transaction clearing rules and government policies (conduct) affect in very particular ways the prices and quantities (performance) in the market. In slow-moving or static markets, SCPP has been a useful predictor of market performance; in faster markets the market dynamics that endogenously develop over time are often too complex to predict with SCPP or other existing modeling techniques. New, more sophisticated combinations of modeling and simulation are needed. Toward developing a good (i.e., socially optimal) water rights market design that can take into account the dynamics inherent in the water sector, we are developing an agent-based model of water rights markets. The model serves two purposes: first, it provides an SCPP-based framework of water rights markets that takes into account the particular structure of

  20. Examining the pathogenesis of breast cancer using a novel agent-based model of mammary ductal epithelium dynamics.

    PubMed

    Chapa, Joaquin; Bourgo, Ryan J; Greene, Geoffrey L; Kulkarni, Swati; An, Gary

    2013-01-01

    The study of the pathogenesis of breast cancer is challenged by the long time-course of the disease process and the multi-factorial nature of generating oncogenic insults. The characterization of the longitudinal pathogenesis of malignant transformation from baseline normal breast duct epithelial dynamics may provide vital insight into the cascading systems failure that leads to breast cancer. To this end, extensive information on the baseline behavior of normal mammary epithelium and breast cancer oncogenesis was integrated into a computational model termed the Ductal Epithelium Agent-Based Model (DEABM). The DEABM is composed of computational agents that behave according to rules established from published cellular and molecular mechanisms concerning breast duct epithelial dynamics and oncogenesis. The DEABM implements DNA damage and repair, cell division, genetic inheritance and simulates the local tissue environment with hormone excretion and receptor signaling. Unrepaired DNA damage impacts the integrity of the genome within individual cells, including a set of eight representative oncogenes and tumor suppressors previously implicated in breast cancer, with subsequent consequences on successive generations of cells. The DEABM reproduced cellular population dynamics seen during the menstrual cycle and pregnancy, and demonstrated the oncogenic effect of known genetic factors associated with breast cancer, namely TP53 and Myc, in simulations spanning ∼40 years of simulated time. Simulations comparing normal to BRCA1-mutant breast tissue demonstrated rates of invasive cancer development similar to published epidemiologic data with respect to both cumulative incidence over time and estrogen-receptor status. Investigation of the modeling of ERα-positive (ER+) tumorigenesis led to a novel hypothesis implicating the transcription factor and tumor suppressor RUNX3. These data suggest that the DEABM can serve as a potentially valuable framework to augment the

  1. Examining the Pathogenesis of Breast Cancer Using a Novel Agent-Based Model of Mammary Ductal Epithelium Dynamics

    PubMed Central

    Chapa, Joaquin; Bourgo, Ryan J.; Greene, Geoffrey L.; Kulkarni, Swati; An, Gary

    2013-01-01

    The study of the pathogenesis of breast cancer is challenged by the long time-course of the disease process and the multi-factorial nature of generating oncogenic insults. The characterization of the longitudinal pathogenesis of malignant transformation from baseline normal breast duct epithelial dynamics may provide vital insight into the cascading systems failure that leads to breast cancer. To this end, extensive information on the baseline behavior of normal mammary epithelium and breast cancer oncogenesis was integrated into a computational model termed the Ductal Epithelium Agent-Based Model (DEABM). The DEABM is composed of computational agents that behave according to rules established from published cellular and molecular mechanisms concerning breast duct epithelial dynamics and oncogenesis. The DEABM implements DNA damage and repair, cell division, genetic inheritance and simulates the local tissue environment with hormone excretion and receptor signaling. Unrepaired DNA damage impacts the integrity of the genome within individual cells, including a set of eight representative oncogenes and tumor suppressors previously implicated in breast cancer, with subsequent consequences on successive generations of cells. The DEABM reproduced cellular population dynamics seen during the menstrual cycle and pregnancy, and demonstrated the oncogenic effect of known genetic factors associated with breast cancer, namely TP53 and Myc, in simulations spanning ∼40 years of simulated time. Simulations comparing normal to BRCA1-mutant breast tissue demonstrated rates of invasive cancer development similar to published epidemiologic data with respect to both cumulative incidence over time and estrogen-receptor status. Investigation of the modeling of ERα-positive (ER+) tumorigenesis led to a novel hypothesis implicating the transcription factor and tumor suppressor RUNX3. These data suggest that the DEABM can serve as a potentially valuable framework to augment the

  2. Using an agent-based model to analyze the dynamic communication network of the immune response

    PubMed Central

    2011-01-01

    An agent-based model capturing several key aspects of complex system dynamics was used to study the emergent properties of the immune response to viral infection. Specific patterns of interactions between leukocyte agents occurring early in the response significantly improved outcome. More interactions at later stages correlated with persistent inflammation and infection. These simulation experiments highlight the importance of commonly overlooked aspects of the immune response and provide insight into these processes at a resolution level exceeding the capabilities of current laboratory technologies. PMID:21247471

  3. Accounting for diffusion in agent based models of reaction-diffusion systems with application to cytoskeletal diffusion.

    PubMed

    Azimi, Mohammad; Jamali, Yousef; Mofrad, Mohammad R K

    2011-01-01

    Diffusion plays a key role in many biochemical reaction systems seen in nature. Scenarios where diffusion behavior is critical can be seen in the cell and subcellular compartments where molecular crowding limits the interaction between particles. We investigate the application of a computational method for modeling the diffusion of molecules and macromolecules in three-dimensional solutions using agent based modeling. This method allows for realistic modeling of a system of particles with different properties such as size, diffusion coefficients, and affinity as well as the environment properties such as viscosity and geometry. Simulations using these movement probabilities yield behavior that mimics natural diffusion. Using this modeling framework, we simulate the effects of molecular crowding on effective diffusion and have validated the results of our model using Langevin dynamics simulations and note that they are in good agreement with previous experimental data. Furthermore, we investigate an extension of this framework where single discrete cells can contain multiple particles of varying size in an effort to highlight errors that can arise from discretization that lead to the unnatural behavior of particles undergoing diffusion. Subsequently, we explore various algorithms that differ in how they handle the movement of multiple particles per cell and suggest an algorithm that properly accommodates multiple particles of various sizes per cell that can replicate the natural behavior of these particles diffusing. Finally, we use the present modeling framework to investigate the effect of structural geometry on the directionality of diffusion in the cell cytoskeleton with the observation that parallel orientation in the structural geometry of actin filaments of filopodia and the branched structure of lamellipodia can give directionality to diffusion at the filopodia-lamellipodia interface.

  4. Simulating Brain Tumor Heterogeneity with a Multiscale Agent-Based Model: Linking Molecular Signatures, Phenotypes and Expansion Rate

    PubMed Central

    Zhang, Le; Strouthos, Costas G.; Wang, Zhihui; Deisboeck, Thomas S.

    2008-01-01

    We have extended our previously developed 3D multi-scale agent-based brain tumor model to simulate cancer heterogeneity and to analyze its impact across the scales of interest. While our algorithm continues to employ an epidermal growth factor receptor (EGFR) gene-protein interaction network to determine the cells’ phenotype, it now adds an implicit treatment of tumor cell adhesion related to the model’s biochemical microenvironment. We simulate a simplified tumor progression pathway that leads to the emergence of five distinct glioma cell clones with different EGFR density and cell ‘search precisions’. The in silico results show that microscopic tumor heterogeneity can impact the tumor system’s multicellular growth patterns. Our findings further confirm that EGFR density results in the more aggressive clonal populations switching earlier from proliferation-dominated to a more migratory phenotype. Moreover, analyzing the dynamic molecular profile that triggers the phenotypic switch between proliferation and migration, our in silico oncogenomics data display spatial and temporal diversity in documenting the regional impact of tumorigenesis, and thus support the added value of multi-site and repeated assessments in vitro and in vivo. Potential implications from this in silico work for experimental and computational studies are discussed. PMID:20047002

  5. On Religion and Language Evolutions Seen Through Mathematical and Agent Based Models

    NASA Astrophysics Data System (ADS)

    Ausloos, M.

    Religions and languages are social variables, like age, sex, wealth or political opinions, to be studied like any other organizational parameter. In fact, religiosity is one of the most important sociological aspects of populations. Languages are also obvious characteristics of the human species. Religions, languages appear though also disappear. All religions and languages evolve and survive when they adapt to the society developments. On the other hand, the number of adherents of a given religion, or the number of persons speaking a language is not fixed in time, - nor space. Several questions can be raised. E.g. from a oscopic point of view : How many religions/languages exist at a given time? What is their distribution? What is their life time? How do they evolve? From a "microscopic" view point: can one invent agent based models to describe oscopic aspects? Do simple evolution equations exist? How complicated must be a model? These aspects are considered in the present note. Basic evolution equations are outlined and critically, though briefly, discussed. Similarities and differences between religions and languages are summarized. Cases can be illustrated with historical facts and data. It is stressed that characteristic time scales are different. It is emphasized that "external fields" are historically very relevant in the case of religions, rending the study more " interesting" within a mechanistic approach based on parity and symmetry of clusters concepts. Yet the modern description of human societies through networks in reported simulations is still lacking some mandatory ingredients, i.e. the non scalar nature of the nodes, and the non binary aspects of nodes and links, though for the latter this is already often taken into account, including directions. From an analytical point of view one can consider a population independently of the others. It is intuitively accepted, but also found from the statistical analysis of the frequency distribution that an

  6. Agent-based modeling of the spread of influenza-like illness in an emergency department: a simulation study.

    PubMed

    Laskowski, Marek; Demianyk, Bryan C P; Witt, Julia; Mukhi, Shamir N; Friesen, Marcia R; McLeod, Robert D

    2011-11-01

    The objective of this paper was to develop an agent-based modeling framework in order to simulate the spread of influenza virus infection on a layout based on a representative hospital emergency department in Winnipeg, Canada. In doing so, the study complements mathematical modeling techniques for disease spread, as well as modeling applications focused on the spread of antibiotic-resistant nosocomial infections in hospitals. Twenty different emergency department scenarios were simulated, with further simulation of four infection control strategies. The agent-based modeling approach represents systems modeling, in which the emergency department was modeled as a collection of agents (patients and healthcare workers) and their individual characteristics, behaviors, and interactions. The framework was coded in C++ using Qt4 libraries running under the Linux operating system. A simple ordinary least squares (OLS) regression was used to analyze the data, in which the percentage of patients that became infected in one day within the simulation was the dependent variable. The results suggest that within the given instance context, patient-oriented infection control policies (alternate treatment streams, masking symptomatic patients) tend to have a larger effect than policies that target healthcare workers. The agent-based modeling framework is a flexible tool that can be made to reflect any given environment; it is also a decision support tool for practitioners and policymakers to assess the relative impact of infection control strategies. The framework illuminates scenarios worthy of further investigation, as well as counterintuitive findings.

  7. Simulating Land-Use Change using an Agent-Based Land Transaction Model

    NASA Astrophysics Data System (ADS)

    Bakker, M. M.; van Dijk, J.; Alam, S. J.

    2013-12-01

    In the densely populated cultural landscapes of Europe, the vast majority of all land is owned by private parties, be it farmers (the majority), nature organizations, property developers, or citizens. Therewith, the vast majority of all land-use change arises from land transactions between different owner types: successful farms expand at the expense of less successful farms, and meanwhile property developers, individual citizens, and nature organizations also actively purchase land. These land transactions are driven by specific properties of the land, by governmental policies, and by the (economic) motives of both buyers and sellers. Climate/global change can affect these drivers at various scales: at the local scale changes in hydrology can make certain land less or more desirable; at the global scale the agricultural markets will affect motives of farmers to buy or sell land; while at intermediate (e.g. provincial) scales property developers and nature conservationists may be encouraged or discouraged to purchase land. The cumulative result of all these transactions becomes manifest in changing land-use patterns, and consequent environmental responses. Within the project Climate Adaptation for Rural Areas an agent-based land-use model was developed that explores the future response of individual land users to climate change, within the context of wider global change (i.e. policy and market change). It simulates the exchange of land among farmers and between farmers and nature organizations and property developers, for a specific case study area in the east of the Netherlands. Results show that local impacts of climate change can result in a relative stagnation in the land market in waterlogged areas. Furthermore, the increase in dairying at the expense of arable cultivation - as has been observed in the area in the past - is slowing down as arable produce shows a favourable trend in the agricultural world market. Furthermore, budgets for nature managers are

  8. Impact of different policies on unhealthy dietary behaviors in an urban adult population: an agent-based simulation model.

    PubMed

    Zhang, Donglan; Giabbanelli, Philippe J; Arah, Onyebuchi A; Zimmerman, Frederick J

    2014-07-01

    Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model. Simulations were performed to contrast the potential effects of various policies on the evolution of dietary decisions. Our model showed that a 20% increase in taxes on fast foods would lower the probability of fast-food consumption by 3 percentage points, whereas improving the visibility of positive social norms by 10%, either through community-based or mass-media campaigns, could improve the consumption of fruits and vegetables by 7 percentage points and lower fast-food consumption by 6 percentage points. Zoning policies had no significant impact. Interventions emphasizing healthy eating norms may be more effective than directly targeting food prices or regulating local food outlets. Agent-based modeling may be a useful tool for testing the population-level effects of various policies within complex systems.

  9. Impact of Different Policies on Unhealthy Dietary Behaviors in an Urban Adult Population: An Agent-Based Simulation Model

    PubMed Central

    Giabbanelli, Philippe J.; Arah, Onyebuchi A.; Zimmerman, Frederick J.

    2014-01-01

    Objectives. Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. Methods. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model. Simulations were performed to contrast the potential effects of various policies on the evolution of dietary decisions. Results. Our model showed that a 20% increase in taxes on fast foods would lower the probability of fast-food consumption by 3 percentage points, whereas improving the visibility of positive social norms by 10%, either through community-based or mass-media campaigns, could improve the consumption of fruits and vegetables by 7 percentage points and lower fast-food consumption by 6 percentage points. Zoning policies had no significant impact. Conclusions. Interventions emphasizing healthy eating norms may be more effective than directly targeting food prices or regulating local food outlets. Agent-based modeling may be a useful tool for testing the population-level effects of various policies within complex systems. PMID:24832414

  10. SASAgent: an agent based architecture for search, retrieval and composition of scientific models.

    PubMed

    Felipe Mendes, Luiz; Silva, Laryssa; Matos, Ely; Braga, Regina; Campos, Fernanda

    2011-07-01

    Scientific computing is a multidisciplinary field that goes beyond the use of computer as machine where researchers write simple texts, presentations or store analysis and results of their experiments. Because of the huge hardware/software resources invested in experiments and simulations, this new approach to scientific computing currently adopted by research groups is well represented by e-Science. This work aims to propose a new architecture based on intelligent agents to search, recover and compose simulation models, generated in the context of research projects related to biological domain. The SASAgent architecture is described as a multi-tier, comprising three main modules, where CelO ontology satisfies requirements put by e-science projects mainly represented by the semantic knowledge base. Preliminary results suggest that the proposed architecture is promising to achieve requirements found in e-Science projects, considering mainly the biological domain. Copyright © 2011 Elsevier Ltd. All rights reserved.

  11. A Spatial-Dynamic Agent-based Model of Energy Crop Introduction in Jiangsu province, China

    NASA Astrophysics Data System (ADS)

    Shu, K.; Schneider, U. A.; Scheffran, J.

    2012-12-01

    Bioenergy, as one promising option to replace a fraction of conventional fossil fuels and lower net greenhouse gas emissions, has gained many countries', in particular developing ones' attention. Their focus is mainly on the design of efficient bioenergy utilization pathways which adapt to both local geographic features and economic conditions. The establishment of a biomass production sector would be the first and pivotal component in the whole industrial chain. Several existing studies have estimated the global biomass for energy potential but arrived at very different results. One reason for the large uncertainty of biomass potential may be ascribed to the diverse nature of biomass leading to different estimates in different circumstances. Therefore, specific research at the local level is essential. Following this thought, our research conducted in the Jiangsu province, a representative region in China, will explore the spatial distribution of biomass production. The employed methodology can also be applied to other locations both in China and similar developing countries if model parameters are adequately adjusted. In this study, we analyze the local situation in the Jiangsu province focusing on the selection of new energy crops, since the cultivation of dedicated crop for energy use is still in experimental phase. We also examine the land use conflict which is especially relevant to China with more than 1.3 billion people and a severe burden on food supply. We develop an agent-based model to find the optimal spatial distribution of biomass (SDA-SDB) in Jiangsu province. Compromising data accessibility and heterogeneity of environmental factors across the province, we resolve our model at county level and consider the aggregated farming community in one county as a single agent. The aim of SDA-SDB is to simulate farmers' decision process of allocating land to either food or energy crops facing limited resources and political targets for bioenergy development

  12. A Parallel Sliding Region Algorithm to Make Agent-Based Modeling Possible for a Large-Scale Simulation: Modeling Hepatitis C Epidemics in Canada.

    PubMed

    Wong, William W L; Feng, Zeny Z; Thein, Hla-Hla

    2016-11-01

    Agent-based models (ABMs) are computer simulation models that define interactions among agents and simulate emergent behaviors that arise from the ensemble of local decisions. ABMs have been increasingly used to examine trends in infectious disease epidemiology. However, the main limitation of ABMs is the high computational cost for a large-scale simulation. To improve the computational efficiency for large-scale ABM simulations, we built a parallelizable sliding region algorithm (SRA) for ABM and compared it to a nonparallelizable ABM. We developed a complex agent network and performed two simulations to model hepatitis C epidemics based on the real demographic data from Saskatchewan, Canada. The first simulation used the SRA that processed on each postal code subregion subsequently. The second simulation processed the entire population simultaneously. It was concluded that the parallelizable SRA showed computational time saving with comparable results in a province-wide simulation. Using the same method, SRA can be generalized for performing a country-wide simulation. Thus, this parallel algorithm enables the possibility of using ABM for large-scale simulation with limited computational resources.

  13. Evaluation of outbreak response immunization in the control of pertussis using agent-based modeling

    PubMed Central

    Qian, Weicheng; Osgood, Nathaniel D.

    2016-01-01

    Background Pertussis control remains a challenge due to recently observed effects of waning immunity to acellular vaccine and suboptimal vaccine coverage. Multiple outbreaks have been reported in different ages worldwide. For certain outbreaks, public health authorities can launch an outbreak response immunization (ORI) campaign to control pertussis spread. We investigated effects of an outbreak response immunization targeting young adolescents in averting pertussis cases. Methods We developed an agent-based model for pertussis transmission representing disease mechanism, waning immunity, vaccination schedule and pathogen transmission in a spatially-explicit 500,000-person contact network representing a typical Canadian Public Health district. Parameters were derived from literature and calibration. We used published cumulative incidence and dose-specific vaccine coverage to calibrate the model’s epidemiological curves. We endogenized outbreak response by defining thresholds to trigger simulated immunization campaigns in the 10–14 age group offering 80% coverage. We ran paired simulations with and without outbreak response immunization and included those resulting in a single ORI within a 10-year span. We calculated the number of cases averted attributable to outbreak immunization campaign in all ages, in the 10–14 age group and in infants. The count of cases averted were tested using Mann–Whitney U test to determine statistical significance. Numbers needed to vaccinate during immunization campaign to prevent a single case in respective age groups were derived from the model. We varied adult vaccine coverage, waning immunity parameters, immunization campaign eligibility and tested stronger vaccination boosting effect in sensitivity analyses. Results 189 qualified paired-runs were analyzed. On average, ORI was triggered every 26 years. On a per-run basis, there were an average of 124, 243 and 429 pertussis cases averted across all age groups within 1, 3 and

  14. Comparison of an Agent-based Model of Disease Propagation with the Generalised SIR Epidemic Model

    DTIC Science & Technology

    2009-08-01

    model in a complex multi -agent social context (including alignment of model parameters, scenarios and underlying assumptions). This validation in...both a wargame and a simulator that allows multi -sided multiplayer wargaming. CAEN’s primary focus is close combat infantry battles and as such it...hours worked. Town cadastral town data is used to match businesses and residences to brick and mortar buildings. The generated families and workforce

  15. An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management

    PubMed Central

    Bongiorno, Christian; Mantegna, Rosario N.

    2017-01-01

    We present an agent based model of the Air Traffic Management socio-technical complex system aiming at modeling the interactions between aircraft and air traffic controllers at a tactical level. The core of the model is given by the conflict detection and resolution module and by the directs module. Directs are flight shortcuts that are given by air controllers to speed up the passage of an aircraft within a certain airspace and therefore to facilitate airline operations. Conflicts between flight trajectories can occur for two main reasons: either the planning of the flight trajectory was not sufficiently detailed to rule out all potential conflicts or unforeseen events during the flight require modifications of the flight plan that can conflict with other flight trajectories. Our model performs a local conflict detection and resolution procedure. Once a flight trajectory has been made conflict-free, the model searches for possible improvements of the system efficiency by issuing directs. We give an example of model calibration based on real data. We then provide an illustration of the capability of our model in generating scenario simulations able to give insights about the air traffic management system. We show that the calibrated model is able to reproduce the existence of a geographical localization of air traffic controllers’ operations. Finally, we use the model to investigate the relationship between directs and conflict resolutions (i) in the presence of perfect forecast ability of controllers, and (ii) in the presence of some degree of uncertainty in flight trajectory forecast. PMID:28419160

  16. An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management.

    PubMed

    Bongiorno, Christian; Miccichè, Salvatore; Mantegna, Rosario N

    2017-01-01

    We present an agent based model of the Air Traffic Management socio-technical complex system aiming at modeling the interactions between aircraft and air traffic controllers at a tactical level. The core of the model is given by the conflict detection and resolution module and by the directs module. Directs are flight shortcuts that are given by air controllers to speed up the passage of an aircraft within a certain airspace and therefore to facilitate airline operations. Conflicts between flight trajectories can occur for two main reasons: either the planning of the flight trajectory was not sufficiently detailed to rule out all potential conflicts or unforeseen events during the flight require modifications of the flight plan that can conflict with other flight trajectories. Our model performs a local conflict detection and resolution procedure. Once a flight trajectory has been made conflict-free, the model searches for possible improvements of the system efficiency by issuing directs. We give an example of model calibration based on real data. We then provide an illustration of the capability of our model in generating scenario simulations able to give insights about the air traffic management system. We show that the calibrated model is able to reproduce the existence of a geographical localization of air traffic controllers' operations. Finally, we use the model to investigate the relationship between directs and conflict resolutions (i) in the presence of perfect forecast ability of controllers, and (ii) in the presence of some degree of uncertainty in flight trajectory forecast.

  17. An Economic Analysis of Strategies to Control Clostridium Difficile Transmission and Infection Using an Agent-Based Simulation Model.

    PubMed

    Nelson, Richard E; Jones, Makoto; Leecaster, Molly; Samore, Matthew H; Ray, William; Huttner, Angela; Huttner, Benedikt; Khader, Karim; Stevens, Vanessa W; Gerding, Dale; Schweizer, Marin L; Rubin, Michael A

    2016-01-01

    A number of strategies exist to reduce Clostridium difficile (C. difficile) transmission. We conducted an economic evaluation of "bundling" these strategies together. We constructed an agent-based computer simulation of nosocomial C. difficile transmission and infection in a hospital setting. This model included the following components: interactions between patients and health care workers; room contamination via C. difficile shedding; C. difficile hand carriage and removal via hand hygiene; patient acquisition of C. difficile via contact with contaminated rooms or health care workers; and patient antimicrobial use. Six interventions were introduced alone and "bundled" together: (a) aggressive C. difficile testing; (b) empiric isolation and treatment of symptomatic patients; (c) improved adherence to hand hygiene and (d) contact precautions; (e) improved use of soap and water for hand hygiene; and (f) improved environmental cleaning. Our analysis compared these interventions using values representing 3 different scenarios: (1) base-case (BASE) values that reflect typical hospital practice, (2) intervention (INT) values that represent implementation of hospital-wide efforts to reduce C. diff transmission, and (3) optimal (OPT) values representing the highest expected results from strong adherence to the interventions. Cost parameters for each intervention were obtained from published literature. We performed our analyses assuming low, normal, and high C. difficile importation prevalence and transmissibility of C. difficile. INT levels of the "bundled" intervention were cost-effective at a willingness-to-pay threshold of $100,000/quality-adjusted life-year in all importation prevalence and transmissibility scenarios. OPT levels of intervention were cost-effective for normal and high importation prevalence and transmissibility scenarios. When analyzed separately, hand hygiene compliance, environmental decontamination, and empiric isolation and treatment were the

  18. An integrated modeling framework of socio-economic, biophysical, and hydrological processes in Midwest landscapes: Remote sensing data, agro-hydrological model, and agent-based model

    NASA Astrophysics Data System (ADS)

    Ding, Deng

    of perennial grasses or corn stover as a more risky enterprise than their current crop production systems, likely because of market and production risks and lock in effects. As a result farmers do not follow a simple farm-profit maximization rule. In the third study, the consequent water quantity and quality change of the potential land use transitions given alternative biofuel crop market scenarios is explored in a case study in the Clear Creek watershed. A computer program is developed to implement the loose-coupling strategy to couple an agent-based land use model with SWAT. The simulation results show that watershed-scale water quantity (water yield and runoff) and quality variables (sediment and nutrient loads) decrease in values as switchgrass price increases. However, negligence of farmers risk aversions towards biofuel crop adoption would cause overestimation of the impacts of switchgrass price on water quantity and quality.

  19. Linking Bayesian and Agent-Based Models to Simulate Complex Social-Ecological Systems in the Sonoran Desert

    NASA Astrophysics Data System (ADS)

    Pope, A.; Gimblett, R.

    2013-12-01

    Interdependencies of ecologic, hydrologic, and social systems challenge traditional approaches to natural resource management in semi-arid regions. As a complex social-ecological system, water demands in the Sonoran Desert from agricultural and urban users often conflicts with water needs for its ecologically-significant riparian corridors. To explore this system, we developed an agent-based model to simulate complex feedbacks between human decisions and environmental conditions. Cognitive mapping in conjunction with stakeholder participation produced a Bayesian model of conditional probabilities of local human decision-making processes resulting to changes in water demand. Probabilities created in the Bayesian model were incorporated into the agent-based model, so that each agent had a unique probability to make a positive decision based on its perceived environment at each point in time and space. By using a Bayesian approach, uncertainty in the human decision-making process could be incorporated. The spatially-explicit agent-based model simulated changes in depth-to-groundwater by well pumping based on an agent's water demand. Depth-to-groundwater was then used as an indicator of unique vegetation guilds within the riparian corridor. Each vegetation guild provides varying levels of ecosystem services, the changes of which, along with changes in depth-to-groundwater, feedback to influence agent behavior. Using this modeling approach allowed us to examine resilience of semi-arid riparian corridors and agent behavior under various scenarios. The insight provided by the model contributes to understanding how specific interventions may alter the complex social-ecological system in the future.

  20. An agent-based model for the bibliometric h-index

    NASA Astrophysics Data System (ADS)

    Ionescu, Georgia; Chopard, Bastien

    2013-10-01

    We model a virtual scientific community in which authors publish and cite articles. Citations are attributed according to a preferential attachment mechanism. From the numerical simulations, the h-index can be computed. This bottom-up approach reproduces well real bibliometric data. We consider two versions of our model. (1) The single-scientist is controlled by two parameters which can be tuned to reproduce the value of the h-index of many real scientists. Moreover, this model shows how the h-index grows with the number of citations, for a fixed number of articles. We also define an average h-index that can be used to compare the scientific productivity of institutions of different sizes. (2) The multi-scientist model considers a population of scientists and allows us to study the impact of removing citations from the low h-index researchers on the community. Simulations on real bibilometric data, as well as the predictions of the model, show that the h-index eco-system can be strongly affected by such a filtering.

  1. A growth model of human papillomavirus type 16 designed from cellular automata and agent-based models.

    PubMed

    Escobar Ospina, María Elena; Perdomo, Jonatan Gómez

    2013-01-01

    This paper presents a conceptual model that is developed upon a characterization of human papillomavirus type 16 (HPV16) which is used to build a simulation prototype of the HPV16 growth process. The human papillomavirus type 16 is the principal virus detected in invasive lesions of cervical cancer, and associated with the greater persistence and prevalence in pre-malignant and malignant lesions. The probability of acquiring an infection with HPV16 is extremely high in sexually active individuals. However, an HPV16 infection can disappear after becoming a histological confirmed case. According to the characterization of HPV16 proposed in this paper, cells as compared to a society behaves as a complex system, i.e., cells behave in a cooperative manner, following a set of rules defined by local interactions among them. Such complex system is defined by combining a cellular automaton and agent-based models. In this way, the behavior of the HPV16 is simulated by allowing the cellular automaton to follow such parameterized behavior rules. Both cross-sectional and prospective studies indicate that HPV16 infection persistence increase the risk of high-grade CIN, as observed in the results provided by the growth simulation model of HPV16. The average growth rate extrapolated over 52 weeks (12 months) and calculated by the model showed a 37.87% growth for CIN1, 35.53% for CIN2 and 16.92% for CIN3. Remarkably, these results are similar to the results obtained and reported by clinical studies. For example, the results obtained using the proposed model for CIN2 and the results obtained by Östör [36], have a differential of 0.53 percentage points while have a differential of 2.23 percentage points with the results obtained by Insinga et al. [51]. Also, for the CIN3, the results obtained using the proposed model, have a differential of 2.92 percentage points with the Insinga et al. [52], results. Through the specification of parameterized behavior rules for HPV16 that are

  2. Understanding agent-based models of financial markets: A bottom-up approach based on order parameters and phase diagrams

    NASA Astrophysics Data System (ADS)

    Lye, Ribin; Tan, James Peng Lung; Cheong, Siew Ann

    2012-11-01

    We describe a bottom-up framework, based on the identification of appropriate order parameters and determination of phase diagrams, for understanding progressively refined agent-based models and simulations of financial markets. We illustrate this framework by starting with a deterministic toy model, whereby N independent traders buy and sell M stocks through an order book that acts as a clearing house. The price of a stock increases whenever it is bought and decreases whenever it is sold. Price changes are updated by the order book before the next transaction takes place. In this deterministic model, all traders based their buy decisions on a call utility function, and all their sell decisions on a put utility function. We then make the agent-based model more realistic, by either having a fraction fb of traders buy a random stock on offer, or a fraction fs of traders sell a random stock in their portfolio. Based on our simulations, we find that it is possible to identify useful order parameters from the steady-state price distributions of all three models. Using these order parameters as a guide, we find three phases: (i) the dead market; (ii) the boom market; and (iii) the jammed market in the phase diagram of the deterministic model. Comparing the phase diagrams of the stochastic models against that of the deterministic model, we realize that the primary effect of stochasticity is to eliminate the dead market phase.

  3. Foundations of “new” social science: Institutional legitimacy from philosophy, complexity science, postmodernism, and agent-based modeling

    PubMed Central

    Henrickson, Leslie; McKelvey, Bill

    2002-01-01

    Since the death of positivism in the 1970s, philosophers have turned their attention to scientific realism, evolutionary epistemology, and the Semantic Conception of Theories. Building on these trends, Campbellian Realism allows social scientists to accept real-world phenomena as criterion variables against which theories may be tested without denying the reality of individual interpretation and social construction. The Semantic Conception reduces the importance of axioms, but reaffirms the role of models and experiments. Philosophers now see models as “autonomous agents” that exert independent influence on the development of a science, in addition to theory and data. The inappropriate molding effects of math models on social behavior modeling are noted. Complexity science offers a “new” normal science epistemology focusing on order creation by self-organizing heterogeneous agents and agent-based models. The more responsible core of postmodernism builds on the idea that agents operate in a constantly changing web of interconnections among other agents. The connectionist agent-based models of complexity science draw on the same conception of social ontology as do postmodernists. These recent developments combine to provide foundations for a “new” social science centered on formal modeling not requiring the mathematical assumptions of agent homogeneity and equilibrium conditions. They give this “new” social science legitimacy in scientific circles that current social science approaches lack. PMID:12011408

  4. Agent based models for testing city evacuation strategies under a flood event as strategy to reduce flood risk

    NASA Astrophysics Data System (ADS)

    Medina, Neiler; Sanchez, Arlex; Nokolic, Igor; Vojinovic, Zoran

    2016-04-01

    This research explores the uses of Agent Based Models (ABM) and its potential to test large scale evacuation strategies in coastal cities at risk from flood events due to extreme hydro-meteorological events with the final purpose of disaster risk reduction by decreasing human's exposure to the hazard. The first part of the paper corresponds to the theory used to build the models such as: Complex adaptive systems (CAS) and the principles and uses of ABM in this field. The first section outlines the pros and cons of using AMB to test city evacuation strategies at medium and large scale. The second part of the paper focuses on the central theory used to build the ABM, specifically the psychological and behavioral model as well as the framework used in this research, specifically the PECS reference model is cover in this section. The last part of this section covers the main attributes or characteristics of human beings used to described the agents. The third part of the paper shows the methodology used to build and implement the ABM model using Repast-Symphony as an open source agent-based modelling and simulation platform. The preliminary results for the first implementation in a region of the island of Sint-Maarten a Dutch Caribbean island are presented and discussed in the fourth section of paper. The results obtained so far, are promising for a further development of the model and its implementation and testing in a full scale city

  5. Foundations of "new" social science: institutional legitimacy from philosophy, complexity science, postmodernism, and agent-based modeling.

    PubMed

    Henrickson, Leslie; McKelvey, Bill

    2002-05-14

    Since the death of positivism in the 1970s, philosophers have turned their attention to scientific realism, evolutionary epistemology, and the Semantic Conception of Theories. Building on these trends, Campbellian Realism allows social scientists to accept real-world phenomena as criterion variables against which theories may be tested without denying the reality of individual interpretation and social construction. The Semantic Conception reduces the importance of axioms, but reaffirms the role of models and experiments. Philosophers now see models as "autonomous agents" that exert independent influence on the development of a science, in addition to theory and data. The inappropriate molding effects of math models on social behavior modeling are noted. Complexity science offers a "new" normal science epistemology focusing on order creation by self-organizing heterogeneous agents and agent-based models. The more responsible core of postmodernism builds on the idea that agents operate in a constantly changing web of interconnections among other agents. The connectionist agent-based models of complexity science draw on the same conception of social ontology as do postmodernists. These recent developments combine to provide foundations for a "new" social science centered on formal modeling not requiring the mathematical assumptions of agent homogeneity and equilibrium conditions. They give this "new" social science legitimacy in scientific circles that current social science approaches lack.

  6. Can longitudinal generalized estimating equation models distinguish network influence and homophily? An agent-based modeling approach to measurement characteristics.

    PubMed

    Sauser Zachrison, Kori; Iwashyna, Theodore J; Gebremariam, Achamyeleh; Hutchins, Meghan; Lee, Joyce M

    2016-12-28

    Connected individuals (or nodes) in a network are more likely to be similar than two randomly selected nodes due to homophily and/or network influence. Distinguishing between these two influences is an important goal in network analysis, and generalized estimating equation (GEE) analyses of longitudinal dyadic network data are an attractive approach. It is not known to what extent such regressions can accurately extract underlying data generating processes. Therefore our primary objective is to determine to what extent, and under what conditions, does the GEE-approach recreate the actual dynamics in an agent-based model. We generated simulated cohorts with pre-specified network characteristics and attachments in both static and dynamic networks, and we varied the presence of homophily and network influence. We then used statistical regression and examined the GEE model performance in each cohort to determine whether the model was able to detect the presence of homophily and network influence. In cohorts with both static and dynamic networks, we find that the GEE models have excellent sensitivity and reasonable specificity for determining the presence or absence of network influence, but little ability to distinguish whether or not homophily is present. The GEE models are a valuable tool to examine for the presence of network influence in longitudinal data, but are quite limited with respect to homophily.

  7. Modeling hairy root tissue growth in in vitro environments using an agent-based, structured growth model.

    PubMed

    Lenk, Felix; Sürmann, Almuth; Oberthür, Patrick; Schneider, Mandy; Steingroewer, Juliane; Bley, Thomas

    2014-06-01

    An agent-based model for simulating the in vitro growth of Beta vulgaris hairy root cultures is described. The model fitting is based on experimental results and can be used as a virtual experimentator for root networks. It is implemented in the JAVA language and is designed to be easily modified to describe the growth of diverse biological root networks. The basic principles of the model are outlined, with descriptions of all of the relevant algorithms using the ODD protocol, and a case study is presented in which it is used to simulate the development of hairy root cultures of beetroot (Beta vulgaris) in a Petri dish. The model can predict various properties of the developing network, including the total root length, branching point distribution, segment distribution and secondary metabolite accumulation. It thus provides valuable information that can be used when optimizing cultivation parameters (e.g., medium composition) and the cultivation environment (e.g., the cultivation temperature) as well as how constructional parameters change the morphology of the root network. An image recognition solution was used to acquire experimental data that were used when fitting the model and to evaluate the agreement between the simulated results and practical experiments. Overall, the case study simulation closely reproduced experimental results for the cultures grown under equivalent conditions to those assumed in the simulation. A 3D-visualization solution was created to display the simulated results relating to the state of the root network and its environment (e.g., oxygen and nutrient levels).

  8. Deciphering chemokine properties by a hybrid agent-based model of Aspergillus fumigatus infection in human alveoli

    PubMed Central

    Pollmächer, Johannes; Figge, Marc Thilo

    2015-01-01

    The ubiquitous airborne fungal pathogen Aspergillus fumigatus is inhaled by humans every day. In the lung, it is able to quickly adapt to the humid environment and, if not removed within a time frame of 4–8 h, the pathogen may cause damage by germination and invasive growth. Applying a to-scale agent-based model of human alveoli to simulate early A. fumigatus infection under physiological conditions, we recently demonstrated that alveolar macrophages require chemotactic cues to accomplish the task of pathogen detection within the aforementioned time frame. The objective of this study is to specify our general prediction on the as yet unidentified chemokine by a quantitative analysis of its expected properties, such as the diffusion coefficient and the rates of secretion and degradation. To this end, the rule-based implementation of chemokine diffusion in the initial agent-based model is revised by numerically solving the spatio-temporal reaction-diffusion equation in the complex structure of the alveolus. In this hybrid agent-based model, alveolar macrophages are represented as migrating agents that are coupled to the interactive layer of diffusing molecule concentrations by the kinetics of chemokine receptor binding, internalization and re-expression. Performing simulations for more than a million virtual infection scenarios, we find that the ratio of secretion rate to the diffusion coefficient is the main indicator for the success of pathogen detection. Moreover, a subdivision of the parameter space into regimes of successful and unsuccessful parameter combination by this ratio is specific for values of the migration speed and the directional persistence time of alveolar macrophages, but depends only weakly on chemokine degradation rates. PMID:26074897

  9. Engaging Youth Through Spatial Socio-Technical Storytelling, Participatory GIS, Agent-Based Modeling, Online Geogames and Action Projects

    NASA Astrophysics Data System (ADS)

    Poplin, A.; Shenk, L.; Krejci, C.; Passe, U.

    2017-09-01

    The main goal of this paper is to present the conceptual framework for engaging youth in urban planning activities that simultaneously create locally meaningful positive change. The framework for engaging youth interlinks the use of IT tools such as geographic information systems (GIS), agent-based modelling (ABM), online serious games, and mobile participatory geographic information systems with map-based storytelling and action projects. We summarize the elements of our framework and the first results gained in the program Community Growers established in a neighbourhood community of Des Moines, the capital of Iowa, USA. We conclude the paper with a discussion and future research directions.

  10. The role of research efficiency in the evolution of scientific productivity and impact: An agent-based model

    NASA Astrophysics Data System (ADS)

    You, Zhi-Qiang; Han, Xiao-Pu; Hadzibeganovic, Tarik

    2016-02-01

    We introduce an agent-based model to investigate the effects of production efficiency (PE) and hot field tracing capability (HFTC) on productivity and impact of scientists embedded in a competitive research environment. Agents compete to publish and become cited by occupying the nodes of a citation network calibrated by real-world citation datasets. Our Monte-Carlo simulations reveal that differences in individual performance are strongly related to PE, whereas HFTC alone cannot provide sustainable academic careers under intensely competitive conditions. Remarkably, the negative effect of high competition levels on productivity can be buffered by elevated research efficiency if simultaneously HFTC is sufficiently low.

  11. Diffusion dynamics and concentration of toxic materials from quantum dots-based nanotechnologies: an agent-based modeling simulation framework

    NASA Astrophysics Data System (ADS)

    Agusdinata, Datu Buyung; Amouie, Mahbod; Xu, Tao

    2015-01-01

    Due to their favorable electrical and optical properties, quantum dots (QDs) nanostructures have found numerous applications including nanomedicine and photovoltaic cells. However, increased future production, use, and disposal of engineered QD products also raise concerns about their potential environmental impacts. The objective of this work is to establish a modeling framework for predicting the diffusion dynamics and concentration of toxic materials released from Trioctylphosphine oxide-capped CdSe. To this end, an agent-based model simulation with reaction kinetics and Brownian motion dynamics was developed. Reaction kinetics is used to model the stability of surface capping agent particularly due to oxidation process. The diffusion of toxic Cd2+ ions in aquatic environment was simulated using an adapted Brownian motion algorithm. A calibrated parameter to reflect sensitivity to reaction rate is proposed. The model output demonstrates the stochastic spatial distribution of toxic Cd2+ ions under different values of proxy environmental factor parameters. With the only chemistry considered was oxidation, the simulation was able to replicate Cd2+ ion release from Thiol-capped QDs in aerated water. The agent-based method is the first to be developed in the QDs application domain. It adds both simplicity of the solubility and rate of release of Cd2+ ions and complexity of tracking of individual atoms of Cd at the same time.

  12. Using Geographic Information Systems to Define and Map Commuting Patterns as Inputs to Agent-Based Models

    PubMed Central

    Chrest, David P.; Wheaton, William D.

    2010-01-01

    By understanding the movement patterns of people, mathematical modelers can develop models that can better analyze and predict the spread of infectious diseases. People can come into close contact in their workplaces. This report describes methods to develop georeferenced commuting patterns that can be used to characterize the work-related movement of US populations and help agent-based modelers predict workplace contacts that result in disease transmission. We used a census data product called “Census Spatial Tabulation: Census Track of Work by Census Tract of Residence (STP64)” as the data source to develop commuting pattern data for agent-based synthesized populations databases and to develop map products to visualize commuting patterns in the United States. The three primary maps we developed show inbound, outbound, and net change levels of inbound versus outbound commuters by census tract for the year 2000. Net change counts of commuters are visualized as elevations. The results can be used to quantify and assign commuting patterns of synthesized populations among different census tracts. PMID:20505785

  13. An agent based model of integrin clustering: Exploring the role of ligand clustering, integrin homo-oligomerization, integrin-ligand affinity, membrane crowdedness and ligand mobility

    NASA Astrophysics Data System (ADS)

    Jamali, Yousef; Jamali, Tahereh; Mofrad, Mohammad R. K.

    2013-07-01

    Integrins are cell-surface protein heterodimers that coordinate cellular responses to mechanochemical cues from the extracellular matrix (ECM) and stimulate the assembly of small adhesion complexes, which are the initial sites of cell-ECM adhesion. Clustering of integrins is known to mediate signaling through a variety of signal transduction pathways. Yet, the molecular mechanisms of integrin clustering are poorly understood. In this paper, we develop computational models, using agent based modeling (ABM) techniques, to explore two key underlying mechanisms of integrin clustering, namely ligand organization and integrin homo-oligomerization. Our models help to shed light on the potential roles ligand clustering and integrin homo-oligomerization may play in controlling integrin clustering. A potential mechanism for the clustering of integrin is discussed and the effects of other parameters such as integrin-ligand affinity, membrane crowdedness and ligand mobility on integrin clustering are examined.

  14. INTEGRATION OF TGF-β AND EGFR BASED SIGNALING PATHWAYS USING AN AGENT BASED MODEL OF EPITHELIAL RESTITUTION

    PubMed Central

    Stern, Jordan R.; Christley, Scott; Zaborina, Olga; Alverdy, John C.; An, Gary

    2013-01-01

    Damage to an epithelial surface disrupts its mechanical and immunologic barrier function and exposes underlying tissues to a potentially hostile external environment. Epithelial restitution occurs quickly to re-establish the barrier, and comprises a major part of the immediate host response to injured tissue. Pathways involving transforming growth factor beta and activation of epidermal growth factor receptor are both of critical importance, although cross-pathway interactions have been poorly characterized. Agent-based modeling has been demonstrated to be useful in integrating disparate bodies of knowledge and demonstrating the dynamic consequences of pathway structures and cellular population behavior, and is used herein to create an in-silico analog of an in-vitro scratch assay. The In-Vitro Scratch Agent-Based Model (IVSABM) consists of agents representing individual epithelial cells in a simulated extracellular matrix. Agents sense signals from the damaged environment and produce effector molecules, leading to their healing behavior. The IVSABM qualitatively matched wound healing dynamics when compared against data from traditional experiments. Putative crosstalk mechanisms were then instantiated into the IVSABM and their relative plausibility examined, suggesting interaction at the receptor tyrosine kinase level. This highlights the utility of dynamic knowledge representation in the integration of pathways previously studied in separate contexts. PMID:23110640

  15. An Economic Analysis of Strategies to Control Clostridium Difficile Transmission and Infection Using an Agent-Based Simulation Model

    PubMed Central

    Nelson, Richard E.; Jones, Makoto; Leecaster, Molly; Samore, Matthew H.; Ray, William; Huttner, Angela; Huttner, Benedikt; Khader, Karim; Stevens, Vanessa W.; Gerding, Dale; Schweizer, Marin L.; Rubin, Michael A.

    2016-01-01

    Background A number of strategies exist to reduce Clostridium difficile (C. difficile) transmission. We conducted an economic evaluation of “bundling” these strategies together. Methods We constructed an agent-based computer simulation of nosocomial C. difficile transmission and infection in a hospital setting. This model included the following components: interactions between patients and health care workers; room contamination via C. difficile shedding; C. difficile hand carriage and removal via hand hygiene; patient acquisition of C. difficile via contact with contaminated rooms or health care workers; and patient antimicrobial use. Six interventions were introduced alone and "bundled" together: (a) aggressive C. difficile testing; (b) empiric isolation and treatment of symptomatic patients; (c) improved adherence to hand hygiene and (d) contact precautions; (e) improved use of soap and water for hand hygiene; and (f) improved environmental cleaning. Our analysis compared these interventions using values representing 3 different scenarios: (1) base-case (BASE) values that reflect typical hospital practice, (2) intervention (INT) values that represent implementation of hospital-wide efforts to reduce C. diff transmission, and (3) optimal (OPT) values representing the highest expected results from strong adherence to the interventions. Cost parameters for each intervention were obtained from published literature. We performed our analyses assuming low, normal, and high C. difficile importation prevalence and transmissibility of C. difficile. Results INT levels of the “bundled” intervention were cost-effective at a willingness-to-pay threshold of $100,000/quality-adjusted life-year in all importation prevalence and transmissibility scenarios. OPT levels of intervention were cost-effective for normal and high importation prevalence and transmissibility scenarios. When analyzed separately, hand hygiene compliance, environmental decontamination, and empiric

  16. Polarization and Belief Dynamics in the Black and White Communities: An Agent-Based Network Model from the Data

    PubMed Central

    Grim, Patrick; Thomas, Stephen B.; Fisher, Steven; Reade, Christopher; Singer, Daniel J.; Garza, Mary A.; Fryer, Craig S.; Chatman, Jamie

    2013-01-01

    Public health care interventions—regarding vaccination, obesity, and HIV, for example—standardly take the form of information dissemination across a community. But information networks can vary importantly between different ethnic communities, as can levels of trust in information from different sources. We use data from the Greater Pittsburgh Random Household Health Survey to construct models of information networks for White and Black communities--models which reflect the degree of information contact between individuals, with degrees of trust in information from various sources correlated with positions in that social network. With simple assumptions regarding belief change and social reinforcement, we use those modeled networks to build dynamic agent-based models of how information can be expected to flow and how beliefs can be expected to change across each community. With contrasting information from governmental and religious sources, the results show importantly different dynamic patterns of belief polarization within the two communities. PMID:25298731

  17. Analysis of Food Hub Commerce and Participation Using Agent-Based Modeling: Integrating Financial and Social Drivers.

    PubMed

    Krejci, Caroline C; Stone, Richard T; Dorneich, Michael C; Gilbert, Stephen B

    2016-02-01

    Factors influencing long-term viability of an intermediated regional food supply network (food hub) were modeled using agent-based modeling techniques informed by interview data gathered from food hub participants. Previous analyses of food hub dynamics focused primarily on financial drivers rather than social factors and have not used mathematical models. Based on qualitative and quantitative data gathered from 22 customers and 11 vendors at a midwestern food hub, an agent-based model (ABM) was created with distinct consumer personas characterizing the range of consumer priorities. A comparison study determined if the ABM behaved differently than a model based on traditional economic assumptions. Further simulation studies assessed the effect of changes in parameters, such as producer reliability and the consumer profiles, on long-term food hub sustainability. The persona-based ABM model produced different and more resilient results than the more traditional way of modeling consumers. Reduced producer reliability significantly reduced trade; in some instances, a modest reduction in reliability threatened the sustainability of the system. Finally, a modest increase in price-driven consumers at the outset of the simulation quickly resulted in those consumers becoming a majority of the overall customer base. Results suggest that social factors, such as desire to support the community, can be more important than financial factors. An ABM of food hub dynamics, based on human factors data gathered from the field, can be a useful tool for policy decisions. Similar approaches can be used for modeling customer dynamics with other sustainable organizations. © 2015, Human Factors and Ergonomics Society.

  18. Anomalous diffusion in the evolution of soccer championship scores: Real data, mean-field analysis, and an agent-based model

    NASA Astrophysics Data System (ADS)

    da Silva, Roberto; Vainstein, Mendeli H.; Gonçalves, Sebastián; Paula, Felipe S. F.

    2013-08-01

    Statistics of soccer tournament scores based on the double round robin system of several countries are studied. Exploring the dynamics of team scoring during tournament seasons from recent years we find evidences of superdiffusion. A mean-field analysis results in a drift velocity equal to that of real data but in a different diffusion coefficient. Along with the analysis of real data we present the results of simulations of soccer tournaments obtained by an agent-based model which successfully describes the final scoring distribution [da Silva , Comput. Phys. Commun.CPHCBZ0010-465510.1016/j.cpc.2012.10.030 184, 661 (2013)]. Such model yields random walks of scores over time with the same anomalous diffusion as observed in real data.

  19. Optimization of municipal solid waste transportation by integrating GIS analysis, equation-based, and agent-based model.

    PubMed

    Nguyen-Trong, Khanh; Nguyen-Thi-Ngoc, Anh; Nguyen-Ngoc, Doanh; Dinh-Thi-Hai, Van

    2017-01-01

    The amount of municipal solid waste (MSW) has been increasing steadily over the last decade by reason of population rising and waste generation rate. In most of the urban areas, disposal sites are usually located outside of the urban areas due to the scarcity of land. There is no fixed route map for transportation. The current waste collection and transportation are already overloaded arising from the lack of facilities and insufficient resources. In this paper, a model for optimizing municipal solid waste collection will be proposed. Firstly, the optimized plan is developed in a static context, and then it is integrated into a dynamic context using multi-agent based modelling and simulation. A case study related to Hagiang City, Vietnam, is presented to show the efficiency of the proposed model. From the optimized results, it has been found that the cost of the MSW collection is reduced by 11.3%.

  20. Incorporating GIS data into an agent-based model to support planning policy making for the development of creative industries

    NASA Astrophysics Data System (ADS)

    Liu, Helin; Silva, Elisabete A.; Wang, Qian

    2016-07-01

    This paper presents an extension to the agent-based model "Creative Industries Development-Urban Spatial Structure Transformation" by incorporating GIS data. Three agent classes, creative firms, creative workers and urban government, are considered in the model, and the spatial environment represents a set of GIS data layers (i.e. road network, key housing areas, land use). With the goal to facilitate urban policy makers to draw up policies locally and optimise the land use assignment in order to support the development of creative industries, the improved model exhibited its capacity to assist the policy makers conducting experiments and simulating different policy scenarios to see the corresponding dynamics of the spatial distributions of creative firms and creative workers across time within a city/district. The spatiotemporal graphs and maps record the simulation results and can be used as a reference by the policy makers to adjust land use plans adaptively at different stages of the creative industries' development process.

  1. Environmental Sustainability and Effects on Urban Micro Region using Agent-Based Modeling of Urbanisation in Select Major Indian Cities

    NASA Astrophysics Data System (ADS)

    Aithal, B. H.

    2015-12-01

    Abstract: Urbanisation has gained momentum with globalization in India. Policy decisions to set up commercial, industrial hubs have fuelled large scale migration, added with population upsurge has contributed to the fast growing urban region that needs to be monitored in order to design sustainable urban cities. Unplanned urbanization have resulted in the growth of peri-urban region referred to as urban sprawl, are often devoid of basic amenities and infrastructure leading to large scale environmental problems that are evident. Remote sensing data acquired through space borne sensors at regular interval helps in understanding urban dynamics aided by Geoinformatics which has proved very effective in mapping and monitoring for sustainable urban planning. Cellular automata (CA) is a robust approach for the spatially explicit simulation of land-use land cover dynamics. CA uses rules, states, conditions that are vital factors in modelling urbanisation. This communication effectively introduces simulation assistances of CA with the agent based modelling supported by its fuzzy characteristics and weightages through analytical hierarchal process (AHP). This has been done considering perceived agents such as industries, natural resource etc. Respective agent's role in development of a particular regions into an urban area has been examined with weights and its influence of each of these agents based on its characteristics functions. Validation was performed obtaining a high kappa coefficient indicating the quality and the allocation performance of the model & validity of the model to predict future projections. The prediction using the proposed model was performed for 2030. Further environmental sustainability of each of these cities are explored such as water features, environment, greenhouse gas emissions, effects on human human health etc., Modeling suggests trend of various land use classes transformation with the spurt in urban expansions based on specific regions and

  2. Nonlinearity in Social Service Evaluation: A Primer on Agent-Based Modeling

    ERIC Educational Resources Information Center

    Israel, Nathaniel; Wolf-Branigin, Michael

    2011-01-01

    Measurement of nonlinearity in social service research and evaluation relies primarily on spatial analysis and, to a lesser extent, social network analysis. Recent advances in geographic methods and computing power, however, allow for the greater use of simulation methods. These advances now enable evaluators and researchers to simulate complex…

  3. Nonlinearity in Social Service Evaluation: A Primer on Agent-Based Modeling

    ERIC Educational Resources Information Center

    Israel, Nathaniel; Wolf-Branigin, Michael

    2011-01-01

    Measurement of nonlinearity in social service research and evaluation relies primarily on spatial analysis and, to a lesser extent, social network analysis. Recent advances in geographic methods and computing power, however, allow for the greater use of simulation methods. These advances now enable evaluators and researchers to simulate complex…

  4. Analyzing the Surface Warfare Operational Effectiveness of an Offshore Patrol Vessel using Agent Based Modeling

    DTIC Science & Technology

    2012-09-01

    Plot ................................................................45 Figure 17. OSN Model Partition Tree Plot (1st Split ...Model Partition Tree Plot (2nd Split ) .......................................................48 Figure 20. OSN Model Actual by Predicted Plot (Gun...Absent & SSM 1 Equipped) ......49 Figure 21. OSN Model Partition Tree Plot ( Splits 1- 4) ...................................................50 Figure 22

  5. Phenotypic transition maps of 3D breast acini obtained by imaging-guided agent-based modeling

    SciTech Connect

    Tang, Jonathan; Enderling, Heiko; Becker-Weimann, Sabine; Pham, Christopher; Polyzos, Aris; Chen, Chen-Yi; Costes, Sylvain V

    2011-02-18

    We introduce an agent-based model of epithelial cell morphogenesis to explore the complex interplay between apoptosis, proliferation, and polarization. By varying the activity levels of these mechanisms we derived phenotypic transition maps of normal and aberrant morphogenesis. These maps identify homeostatic ranges and morphologic stability conditions. The agent-based model was parameterized and validated using novel high-content image analysis of mammary acini morphogenesis in vitro with focus on time-dependent cell densities, proliferation and death rates, as well as acini morphologies. Model simulations reveal apoptosis being necessary and sufficient for initiating lumen formation, but cell polarization being the pivotal mechanism for maintaining physiological epithelium morphology and acini sphericity. Furthermore, simulations highlight that acinus growth arrest in normal acini can be achieved by controlling the fraction of proliferating cells. Interestingly, our simulations reveal a synergism between polarization and apoptosis in enhancing growth arrest. After validating the model with experimental data from a normal human breast line (MCF10A), the system was challenged to predict the growth of MCF10A where AKT-1 was overexpressed, leading to reduced apoptosis. As previously reported, this led to non growth-arrested acini, with very large sizes and partially filled lumen. However, surprisingly, image analysis revealed a much lower nuclear density than observed for normal acini. The growth kinetics indicates that these acini grew faster than the cells comprising it. The in silico model could not replicate this behavior, contradicting the classic paradigm that ductal carcinoma in situ is only the result of high proliferation and low apoptosis. Our simulations suggest that overexpression of AKT-1 must also perturb cell-cell and cell-ECM communication, reminding us that extracellular context can dictate cellular behavior.

  6. The potential of agent-based modelling for verification of people trajectories based on smartphone sensor data

    NASA Astrophysics Data System (ADS)

    Hillen, F.; Höfle, B.; Ehlers, M.; Reinartz, P.

    2014-02-01

    In this paper the potential of smartphone sensor data for verification of people trajectories derived from airborne remote sensing data are investigated and discussed based on simulated test recordings in the city of Osnabrueck, Germany. For this purpose, the airborne imagery is simulated by images taken from a high building with a typical single lens reflex camera. The smartphone data required for the analysis of the potential is simultaneously recorded by test persons on the ground. In a second step, the quality of the smartphone sensor data is evaluated regarding the integration into simulation and modelling approaches. In this context we studied the potential of the agent-based modelling technique concerning the verification of people trajectories.

  7. Frequency analysis of tick quotes on the foreign exchange market and agent-based modeling: A spectral distance approach

    NASA Astrophysics Data System (ADS)

    Sato, Aki-Hiro

    2007-08-01

    High-frequency financial data of the foreign exchange market (EUR/CHF, EUR/GBP, EUR/JPY, EUR/NOK, EUR/SEK, EUR/USD, NZD/USD, USD/CAD, USD/CHF, USD/JPY, USD/NOK, and USD/SEK) are analyzed by utilizing the Kullback-Leibler divergence between two normalized spectrograms of the tick frequency and the generalized Jensen-Shannon divergence among them. The temporal structure variations of the similarity between currency pairs is detected and characterized. A simple agent-based model in which N market participants exchange M currency pairs is proposed. The equation for the tick frequency is approximately derived theoretically. Based on the analysis of this model, the spectral distance of the tick frequency is associated with the similarity of the behavior (perception and decision) of the market participants in exchanging these currency pairs.

  8. Entrainment and Control of Bacterial Populations: An in Silico Study over a Spatially Extended Agent Based Model.

    PubMed

    Mina, Petros; Tsaneva-Atanasova, Krasimira; Bernardo, Mario di

    2016-07-15

    We extend a spatially explicit agent based model (ABM) developed previously to investigate entrainment and control of the emergent behavior of a population of synchronized oscillating cells in a microfluidic chamber. Unlike most of the work in models of control of cellular systems which focus on temporal changes, we model individual cells with spatial dependencies which may contribute to certain behavioral responses. We use the model to investigate the response of both open loop and closed loop strategies, such as proportional control (P-control), proportional-integral control (PI-control) and proportional-integral-derivative control (PID-control), to heterogeinities and growth in the cell population, variations of the control parameters and spatial effects such as diffusion in the spatially explicit setting of a microfluidic chamber setup. We show that, as expected from the theory of phase locking in dynamical systems, open loop control can only entrain the cell population in a subset of forcing periods, with a wide variety of dynamical behaviors obtained outside these regions of entrainment. Closed-loop control is shown instead to guarantee entrainment in a much wider region of control parameter space although presenting limitations when the population size increases over a certain threshold. In silico tracking experiments are also performed to validate the ability of classical control approaches to achieve other reference behaviors such as a desired constant output or a linearly varying one. All simulations are carried out in BSim, an advanced agent-based simulator of microbial population which is here extended ad hoc to include the effects of control strategies acting onto the population.

  9. [The assessment of the action of pharmacological agents based on a new computer program for analysing animal operant behavior].

    PubMed

    Garibova, T L; Voronina, T A; Stefankov, D V; Kalinina, T S

    1990-01-01

    The new programme is developed for the experimental automatization and analysis of animal operant behavior in Skinner's box (Lafayette Instrument Co., USA) by means of the Apple 2e computer (USA). The fundamental of the programme is the division of the training procedure into different functional intervals. Operant behavior of rats is determined by diverse schedules of food and water reinforcement and electric shock. Rats were trained to response on schedules FR 20, FI 1, drug discrimination. Phenazepam (2 mg/kg) markedly decreases the number of responses on schedule FR 20. Phenazepam is a discriminable stimulus. The experimental results make it possible to use the programme for modelling various forms of operant behavior and analysing pharmacological properties of the well-known and new drugs.

  10. Particle Swarm Social Adaptive Model for Multi-Agent Based Insurgency Warfare Simulation

    SciTech Connect

    Cui, Xiaohui; Potok, Thomas E

    2009-12-01

    To better understand insurgent activities and asymmetric warfare, a social adaptive model for modeling multiple insurgent groups attacking multiple military and civilian targets is proposed and investigated. This report presents a pilot study using the particle swarm modeling, a widely used non-linear optimal tool to model the emergence of insurgency campaign. The objective of this research is to apply the particle swarm metaphor as a model of insurgent social adaptation for the dynamically changing environment and to provide insight and understanding of insurgency warfare. Our results show that unified leadership, strategic planning, and effective communication between insurgent groups are not the necessary requirements for insurgents to efficiently attain their objective.

  11. A place for agent-based models. Comment on "Statistical physics of crime: A review" by M.R. D'Orsogna and M. Perc

    NASA Astrophysics Data System (ADS)

    Barbaro, Alethea

    2015-03-01

    Agent-based models have been widely applied in theoretical ecology to explain migrations and other collective animal movements [2,5,8]. As D'Orsogna and Perc have expertly highlighted in [6], the recent emergence of crime modeling has opened another interesting avenue for mathematical investigation. The area of crime modeling is particularly suited to agent-based models, because these models offer a great deal of flexibility within the model and also ease of communication among criminologist, law enforcement and modelers.

  12. An agent-based modeling framework for evaluating hypotheses on risks for developing autism: effects of the gut microbial environment.

    PubMed

    Weston, Bronson; Fogal, Benjamin; Cook, Daniel; Dhurjati, Prasad

    2015-04-01

    The number of cases diagnosed with Autism Spectrum Disorders is rising at an alarming rate with the Centers for Disease Control estimating the 2014 incidence rate as 1 in 68. Recently, it has been hypothesized that gut bacteria may contribute to the development of autism. Specifically, the relative balances between the inflammatory microbes clostridia and desulfovibrio and the anti-inflammatory microbe bifidobacteria may become destabilized prior to autism development. The imbalance leads to a leaky gut, characterized by a more porous epithelial membrane resulting in microbial toxin release into the blood, which may contribute to brain inflammation and autism development. To test how changes in population dynamics of the gut microbiome may lead to the imbalanced microbial populations associated with autism patients, we constructed a novel agent-based model of clostridia, desulfovibrio, and bifidobacteria population interactions in the gut. The model demonstrates how changing physiological conditions in the gut can affect the population dynamics of the microbiome. Simulations using our agent-based model indicate that despite large perturbations to initial levels of bacteria, the populations robustly achieve a single steady-state given similar gut conditions. These simulation results suggests that disturbance such as a prebiotic or antibiotic treatment may only transiently affect the gut microbiome. However, sustained prebiotic treatments may correct low population counts of bifidobacteria. Furthermore, our simulations suggest that clostridia growth rate is a key determinant of risk of autism development. Treatment of high-risk infants with supra-physiological levels of lysozymes may suppress clostridia growth rate, resulting in a steep decrease in the clostridia population and therefore reduced risk of autism development.

  13. Approach and development strategy for an agent-based model of economic confidence.

    SciTech Connect

    Sprigg, James A.; Pryor, Richard J.; Jorgensen, Craig Reed

    2004-08-01

    We are extending the existing features of Aspen, a powerful economic modeling tool, and introducing new features to simulate the role of confidence in economic activity. The new model is built from a collection of autonomous agents that represent households, firms, and other relevant entities like financial exchanges and governmental authorities. We simultaneously model several interrelated markets, including those for labor, products, stocks, and bonds. We also model economic tradeoffs, such as decisions of households and firms regarding spending, savings, and investment. In this paper, we review some of the basic principles and model components and describe our approach and development strategy for emulating consumer, investor, and business confidence. The model of confidence is explored within the context of economic disruptions, such as those resulting from disasters or terrorist events.

  14. Agent-Based Modeling of Physical Factors That May Control the Growth of Coccidioides immitis (Valley Fever Fungus) in Soils

    NASA Astrophysics Data System (ADS)

    Gettings, M. E.; Fisher, F. S.

    2003-12-01

    A model of the spread and survival of the fungus Coccidioides immitis in soil via wind-borne spore transport has been completed using public domain agent-based modeling software. The hypothetical model posits that for a successful new site to become established, four factors must be simultaneously satisfied. 1) There must be transport of spores from a source site to sites with favorable soil geology, texture, topographic aspect, and lack of biomass competition. 2) There must be sufficient moisture for fungal growth. 3) Temperature of the surface and soil must be favorable for growth. Finally, 4) the temperature and moisture must remain in favorable ranges for a long enough time interval for the fungus to grow down to depths at which spores will survive subsequent heat, aridity, and ultraviolet radiation of the hot, dry season typical of the Southwest U.S. climate. Using agent-based modeling software, a model was built so that the effects of combinations of these controlling factors could be evaluated using realistic temperature, rain and wind models. The rain probability and amount, temperature annual and diurnal variation, and wind direction and intensity were based on the weather records at Tucson, Arizona for the 107-year period from 1894 to 2001. Favorable ground was defined using a fractal tree algorithm that emulates a drainage network in accordance with observations that favorable sites are often adjacent to drainage channels. Numerous model runs produced the following five conclusions. 1) If any property is not isotropic, for example wind direction or narrow paths of rainstorms, parts of the favorable areas will never become colonized no matter how long the model runs. 2)The spread of sites is extremely sensitive to moisture duration. The amount of wind and temperature after a rain control the length of time before a site becomes too dry. 3) The distribution of wind and rainstorm direction relative to that of the favorable sites is a strong control on the

  15. An Agent-based Model Simulation of Multiple Collaborating Mobile Ad Hoc Networks (MANET)

    DTIC Science & Technology

    2011-06-01

    RESULTS: Agent Learning Profiles Discounted Positive Reinforcement Learning Learning and Forgetting Forgetting is triggered by task conditions that...disable rational and deliberate mental models –forcing the agent to ignore (or forget) routine processes. Positive reinforcement is earned by an...deliberate behavior of agents as rational entities (model-based functions). 6.Experiment with positive reinforcement learning (with incremental gain over

  16. Understanding the relationship between safety investment and safety performance of construction projects through agent-based modeling.

    PubMed

    Lu, Miaojia; Cheung, Clara Man; Li, Heng; Hsu, Shu-Chien

    2016-09-01

    The construction industry in Hong Kong increased its safety investment by 300% in the past two decades; however, its accident rate has plateaued to around 50% for one decade. Against this backdrop, researchers have found inconclusive results on the causal relationship between safety investment and safety performance. Using agent-based modeling, this study takes an unconventional bottom-up approach to study safety performance on a construction site as an outcome of a complex system defined by interactions among a worksite, individual construction workers, and different safety investments. Instead of focusing on finding the absolute relationship between safety investment and safety performance, this study contributes to providing a practical framework to investigate how different safety investments interacting with different parameters such as human and environmental factors could affect safety performance. As a result, we could identify cost-effective safety investments under different construction scenarios for delivering optimal safety performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Theory of agent-based market models with controlled levels of greed and anxiety

    NASA Astrophysics Data System (ADS)

    Papadopoulos, P.; Coolen, A. C. C.

    2010-01-01

    We use generating functional analysis to study minority-game-type market models with generalized strategy valuation updates that control the psychology of agents' actions. The agents' choice between trend-following and contrarian trading, and their vigor in each, depends on the overall state of the market. Even in 'fake history' models, the theory now involves an effective overall bid process (coupled to the effective agent process) which can exhibit profound remanence effects and new phase transitions. For some models the bid process can be solved directly, others require Maxwell-construction-type approximations.