Science.gov

Sample records for agent-based social simulation

  1. 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).

  2. 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).

  3. An Agent-Based Epidemic Simulation of Social Behaviors Affecting HIV Transmission among Taiwanese Homosexuals

    PubMed Central

    2015-01-01

    Computational simulations are currently used to identify epidemic dynamics, to test potential prevention and intervention strategies, and to study the effects of social behaviors on HIV transmission. The author describes an agent-based epidemic simulation model of a network of individuals who participate in high-risk sexual practices, using number of partners, condom usage, and relationship length to distinguish between high- and low-risk populations. Two new concepts—free links and fixed links—are used to indicate tendencies among individuals who either have large numbers of short-term partners or stay in long-term monogamous relationships. An attempt was made to reproduce epidemic curves of reported HIV cases among male homosexuals in Taiwan prior to using the agent-based model to determine the effects of various policies on epidemic dynamics. Results suggest that when suitable adjustments are made based on available social survey statistics, the model accurately simulates real-world behaviors on a large scale. PMID:25815047

  4. The effects of social interactions on fertility decline in nineteenth-century France: an agent-based simulation experiment.

    PubMed

    González-Bailón, Sandra; Murphy, Tommy E

    2013-07-01

    We built an agent-based simulation, incorporating geographic and demographic data from nineteenth-century France, to study the role of social interactions in fertility decisions. The simulation made experimentation possible in a context where other empirical strategies were precluded by a lack of data. We evaluated how different decision rules, with and without interdependent decision-making, caused variations in population growth and fertility levels. The analyses show that incorporating social influence into the model allows empirically observed behaviour to be mimicked, especially at a national level. These findings shed light on individual-level mechanisms through which the French demographic transition may have developed.

  5. 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.

  6. An Empirical Agent-Based Model to Simulate the Adoption of Water Reuse Using the Social Amplification of Risk Framework.

    PubMed

    Kandiah, Venu; Binder, Andrew R; Berglund, Emily Z

    2017-01-11

    Water reuse can serve as a sustainable alternative water source for urban areas. However, the successful implementation of large-scale water reuse projects depends on community acceptance. Because of the negative perceptions that are traditionally associated with reclaimed water, water reuse is often not considered in the development of urban water management plans. This study develops a simulation model for understanding community opinion dynamics surrounding the issue of water reuse, and how individual perceptions evolve within that context, which can help in the planning and decision-making process. Based on the social amplification of risk framework, our agent-based model simulates consumer perceptions, discussion patterns, and their adoption or rejection of water reuse. The model is based on the "risk publics" model, an empirical approach that uses the concept of belief clusters to explain the adoption of new technology. Each household is represented as an agent, and parameters that define their behavior and attributes are defined from survey data. Community-level parameters-including social groups, relationships, and communication variables, also from survey data-are encoded to simulate the social processes that influence community opinion. The model demonstrates its capabilities to simulate opinion dynamics and consumer adoption of water reuse. In addition, based on empirical data, the model is applied to investigate water reuse behavior in different regions of the United States. Importantly, our results reveal that public opinion dynamics emerge differently based on membership in opinion clusters, frequency of discussion, and the structure of social networks.

  7. Agent Based Simulation Output Analysis

    DTIC Science & Technology

    2011-12-01

    over long periods of time) not to have a steady state, but apparently does. These simulation models are available free from sigmawiki.com 2.1...are used in computer animations and movies (for example, in the movie Jurassic Park) as well as to look for emergent social behavior in groups

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. Agent-Based Simulations for Project Management

    NASA Technical Reports Server (NTRS)

    White, J. Chris; Sholtes, Robert M.

    2011-01-01

    Currently, the most common approach used in project planning tools is the Critical Path Method (CPM). While this method was a great improvement over the basic Gantt chart technique being used at the time, it now suffers from three primary flaws: (1) task duration is an input, (2) productivity impacts are not considered , and (3) management corrective actions are not included. Today, computers have exceptional computational power to handle complex simulations of task e)(eculion and project management activities (e.g ., dynamically changing the number of resources assigned to a task when it is behind schedule). Through research under a Department of Defense contract, the author and the ViaSim team have developed a project simulation tool that enables more realistic cost and schedule estimates by using a resource-based model that literally turns the current duration-based CPM approach "on its head." The approach represents a fundamental paradigm shift in estimating projects, managing schedules, and reducing risk through innovative predictive techniques.

  14. Solution of partial differential equations by agent-based simulation

    NASA Astrophysics Data System (ADS)

    Szilagyi, Miklos N.

    2014-01-01

    The purpose of this short note is to demonstrate that partial differential equations can be quickly solved by agent-based simulation with high accuracy. There is no need for the solution of large systems of algebraic equations. This method is especially useful for quick determination of potential distributions and demonstration purposes in teaching electromagnetism.

  15. 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.

  16. Serious games experiment toward agent-based simulation

    USGS Publications Warehouse

    Wein, Anne; Labiosa, William

    2013-01-01

    We evaluate the potential for serious games to be used as a scientifically based decision-support product that supports the United States Geological Survey’s (USGS) mission--to provide integrated, unbiased scientific information that can make a substantial contribution to societal well-being for a wide variety of complex environmental challenges. Serious or pedagogical games are an engaging way to educate decisionmakers and stakeholders about environmental challenges that are usefully informed by natural and social scientific information and knowledge and can be designed to promote interactive learning and exploration in the face of large uncertainties, divergent values, and complex situations. We developed two serious games that use challenging environmental-planning issues to demonstrate and investigate the potential contributions of serious games to inform regional-planning decisions. Delta Skelta is a game emulating long-term integrated environmental planning in the Sacramento-San Joaquin Delta, California, that incorporates natural hazards (flooding and earthquakes) and consequences for California water supplies amidst conflicting water interests. Age of Ecology is a game that simulates interactions between economic and ecologic processes, as well as natural hazards while implementing agent-based modeling. The content of these games spans the USGS science mission areas related to water, ecosystems, natural hazards, land use, and climate change. We describe the games, reflect on design and informational aspects, and comment on their potential usefulness. During the process of developing these games, we identified various design trade-offs involving factual information, strategic thinking, game-winning criteria, elements of fun, number and type of players, time horizon, and uncertainty. We evaluate the two games in terms of accomplishments and limitations. Overall, we demonstrated the potential for these games to usefully represent scientific information

  17. 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.

  18. 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

  19. 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.

  20. A Participatory Agent-Based Simulation for Indoor Evacuation Supported by Google Glass

    PubMed Central

    Sánchez, Jesús M.; Carrera, Álvaro; Iglesias, Carlos Á.; Serrano, Emilio

    2016-01-01

    Indoor evacuation systems are needed for rescue and safety management. One of the challenges is to provide users with personalized evacuation routes in real time. To this end, this project aims at exploring the possibilities of Google Glass technology for participatory multiagent indoor evacuation simulations. Participatory multiagent simulation combines scenario-guided agents and humans equipped with Google Glass that coexist in a shared virtual space and jointly perform simulations. The paper proposes an architecture for participatory multiagent simulation in order to combine devices (Google Glass and/or smartphones) with an agent-based social simulator and indoor tracking services. PMID:27563911

  1. A Participatory Agent-Based Simulation for Indoor Evacuation Supported by Google Glass.

    PubMed

    Sánchez, Jesús M; Carrera, Álvaro; Iglesias, Carlos Á; Serrano, Emilio

    2016-08-24

    Indoor evacuation systems are needed for rescue and safety management. One of the challenges is to provide users with personalized evacuation routes in real time. To this end, this project aims at exploring the possibilities of Google Glass technology for participatory multiagent indoor evacuation simulations. Participatory multiagent simulation combines scenario-guided agents and humans equipped with Google Glass that coexist in a shared virtual space and jointly perform simulations. The paper proposes an architecture for participatory multiagent simulation in order to combine devices (Google Glass and/or smartphones) with an agent-based social simulator and indoor tracking services.

  2. Agent-based simulation of a financial market

    NASA Astrophysics Data System (ADS)

    Raberto, Marco; Cincotti, Silvano; Focardi, Sergio M.; Marchesi, Michele

    2001-10-01

    This paper introduces an agent-based artificial financial market in which heterogeneous agents trade one single asset through a realistic trading mechanism for price formation. Agents are initially endowed with a finite amount of cash and a given finite portfolio of assets. There is no money-creation process; the total available cash is conserved in time. In each period, agents make random buy and sell decisions that are constrained by available resources, subject to clustering, and dependent on the volatility of previous periods. The model proposed herein is able to reproduce the leptokurtic shape of the probability density of log price returns and the clustering of volatility. Implemented using extreme programming and object-oriented technology, the simulator is a flexible computational experimental facility that can find applications in both academic and industrial research projects.

  3. 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.

  4. 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).

  5. 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.

  6. 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.

  7. Network Interventions on Physical Activity in an Afterschool Program: An Agent-Based Social Network Study

    PubMed Central

    Zhang, Jun; Shoham, David A.; Tesdahl, Eric

    2015-01-01

    Objectives. We studied simulated interventions that leveraged social networks to increase physical activity in children. Methods. We studied a real-world social network of 81 children (average age = 7.96 years) who lived in low socioeconomic status neighborhoods, and attended public schools and 1 of 2 structured afterschool programs. The sample was ethnically diverse, and 44% were overweight or obese. We used social network analysis and agent-based modeling simulations to test whether implementing a network intervention would increase children’s physical activity. We tested 3 intervention strategies. Results. The intervention that targeted opinion leaders was effective in increasing the average level of physical activity across the entire network. However, the intervention that targeted the most sedentary children was the best at increasing their physical activity levels. Conclusions. Which network intervention to implement depends on whether the goal is to shift the entire distribution of physical activity or to influence those most adversely affected by low physical activity. Agent-based modeling could be an important complement to traditional project planning tools, analogous to sample size and power analyses, to help researchers design more effective interventions for increasing children’s physical activity. PMID:25689202

  8. Identifying Evacuees' Demand of Tsunami Shelters using Agent Based Simulation

    NASA Astrophysics Data System (ADS)

    Mas, E.; Adriano, B.; Koshimura, S.; Imamura, F.; Kuroiwa, J.; Yamazaki, F.; Zavala, C.; Estrada, M.

    2012-12-01

    Amongst the lessons learned in tsunami events such as the 2004 Indian Ocean and 2011 Great Tohoku Japan earthquake is that sometimes nature exceeds structural countermeasures like seawalls, breakwaters or tsunami gates. In such situations it is a challenging task for people in plain areas to find sheltering places. The vertical evacuation to multistory buildings is one alternative to provide areas for sheltering in a complex environment of evacuation. However, if the spatial distribution and the available capacity of these structures are not well displayed, conditions of evacuee over-demand or under-demand might be observed in several structures. In this study, we present the integration of the tsunami numerical modeling and the agent based simulation of evacuation as the method to estimate the sheltering demand of evacuees in an emergent behavior approach. The case study is set in La Punta district in Peru. Here, we used in the tsunami simulation a seismic source of slip distribution model (Pulido et.al. ,2011; Chlieh et.al, 2011) for a possible future tsunami scenario in the central Andes. We modeled three alternatives of evacuation. First, the horizontal evacuation scenario was analyzed to support the necessity of the sheltering-in-place option for the district. Second, the vertical evacuation scenario and third, the combination of vertical and horizontal evacuation scenarios of pedestrians and vehicles were conducted. In the last two alternatives, the demand of evacuees were measured at each official tsunami evacuation building and compared to the sheltering capacity of the structure. Results showed that out of twenty tsunami evacuation buildings, thirteen resulted with over-demands and seven were still with available space. Also it is confirmed that in this case the horizontal evacuation might lead to a high number of casualties due to the traffic congestion at the neck of the district. Finally the vertical evacuation would be a suitable solution for this area

  9. Agent-based Approaches to Dynamic Team Simulation

    DTIC Science & Technology

    2008-09-01

    behavior. The second section reviews agent-based models of teamwork describing work involving both teamwork approaches to design of multiagent systems...there is less direct evidence for teams. Hough (1992), for example, found that ratings on conscientiousness, emotional stability, and agreeableness...Peeters, Rutte, Tuijl, and Reymen (2006) who found agreeableness and emotional stability positively related to satisfaction with the team make

  10. 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

  11. AN AGENT-BASED SIMULATION STUDY OF A COMPLEX ADAPTIVE COLLABORATION NETWORK

    SciTech Connect

    Ozmen, Ozgur; Smith, Jeffrey; Yilmaz, Levent

    2013-01-01

    One of the most significant problems in organizational scholarship is to discern how social collectives govern, organize, and coordinate the actions of individuals to achieve collective outcomes. The collectives are usually interpreted as complex adaptive systems (CAS). The understanding of CAS is more likely to arise with the help of computer-based simulations. In this tutorial, using agent-based modeling approach, a complex adaptive social communication network model is introduced. The objective is to present the underlying dynamics of the system in a form of computer simulation that enables analyzing the impacts of various mechanisms on network topologies and emergent behaviors. The ultimate goal is to further our understanding of the dynamics in the system and facilitate developing informed policies for decision-makers.

  12. 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).…

  13. 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.

  14. Multi-Agent-Based Simulation of a Complex Ecosystem of Mental Health Care.

    PubMed

    Kalton, Alan; Falconer, Erin; Docherty, John; Alevras, Dimitris; Brann, David; Johnson, Kyle

    2016-02-01

    This paper discusses the creation of an Agent-Based Simulation that modeled the introduction of care coordination capabilities into a complex system of care for patients with Serious and Persistent Mental Illness. The model describes the engagement between patients and the medical, social and criminal justice services they interact with in a complex ecosystem of care. We outline the challenges involved in developing the model, including process mapping and the collection and synthesis of data to support parametric estimates, and describe the controls built into the model to support analysis of potential changes to the system. We also describe the approach taken to calibrate the model to an observable level of system performance. Preliminary results from application of the simulation are provided to demonstrate how it can provide insights into potential improvements deriving from introduction of care coordination technology.

  15. Agent Based Simulation Design for Aggregation and Disaggregation

    DTIC Science & Technology

    2011-12-01

    Development of a Generic Data-Driven Simulation.‖ In Proceed- ings of the 2010 Winter Simulation Conference, edited by B. Johansson, S. Jain, J. Montoya ...DARPA, Santa Monica, CA. Davis, P. and R. Hillestad. 1993. ―Families of Models that Cross Levels of Resolution: Issues for Design, Calibration and...Issues, and Prin- ciples.‖ RAND N-3400-DARPA, Santa Monica, CA. Department of Defense. 1995. ―Department of Defense Modeling and Simulation Master

  16. Prediction Markets and Beliefs about Climate: Results from Agent-Based Simulations

    NASA Astrophysics Data System (ADS)

    Gilligan, J. M.; John, N. J.; van der Linden, M.

    2015-12-01

    Climate scientists have long been frustrated by persistent doubts a large portion of the public expresses toward the scientific consensus about anthropogenic global warming. The political and ideological polarization of this doubt led Vandenbergh, Raimi, and Gilligan [1] to propose that prediction markets for climate change might influence the opinions of those who mistrust the scientific community but do trust the power of markets.We have developed an agent-based simulation of a climate prediction market in which traders buy and sell future contracts that will pay off at some future year with a value that depends on the global average temperature at that time. The traders form a heterogeneous population with different ideological positions, different beliefs about anthropogenic global warming, and different degrees of risk aversion. We also vary characteristics of the market, including the topology of social networks among the traders, the number of traders, and the completeness of the market. Traders adjust their beliefs about climate according to the gains and losses they and other traders in their social network experience. This model predicts that if global temperature is predominantly driven by greenhouse gas concentrations, prediction markets will cause traders' beliefs to converge toward correctly accepting anthropogenic warming as real. This convergence is largely independent of the structure of the market and the characteristics of the population of traders. However, it may take considerable time for beliefs to converge. Conversely, if temperature does not depend on greenhouse gases, the model predicts that traders' beliefs will not converge. We will discuss the policy-relevance of these results and more generally, the use of agent-based market simulations for policy analysis regarding climate change, seasonal agricultural weather forecasts, and other applications.[1] MP Vandenbergh, KT Raimi, & JM Gilligan. UCLA Law Rev. 61, 1962 (2014).

  17. 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

  18. A Conceptual Framework for Representing Human Behavior Characteristics in a System of Systems Agent-Based Survivability Simulation

    DTIC Science & Technology

    2010-11-22

    distribution is unlimited. A CONCEPTUAL FRAMEWORK FOR REPRESENTING HUMAN BEHAVIOR CHARACTERISTICS IN A SYSTEM OF SYSTEMS AGENT-BASED SURVIVABILITY...27411 -0001 ABSTRACT A CONCEPTUAL FRAMEWORK FOR REPRESENTING HUMAN BEHAVIOR CHARACTERISTICS IN A SYSTEM OF SYSTEMS AGENT-BASED SURVIVABILITY SIMULATION...TITLE AND SUBTITLE A CONCEPTUAL FRAMEWORK FOR REPRESENTING HUMAN BEHAVIOR CHARACTERISTICS IN A SYSTEM OF SYSTEMS AGENT-BASED SURVIVABILITY

  19. Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent-Based Simulation.

    PubMed

    Kroshl, William M; Sarkani, Shahram; Mazzuchi, Thomas A

    2015-09-01

    This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg "leader follower" game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach.

  20. 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.

  1. 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.

  2. An agent-based simulation of extirpation of Ceratitis capitata applied to invasions in California

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We describe and validate an Agent-Based Simulation(ABS) of invasive insects and use it to investigate the time to extirpation of Ceratitis capitata using data from seven outbreaks that occurred in California from 2008-2010. Results are compared with the length of intervention and quarantine imposed ...

  3. Dynamic impact of social stratification and social influence on smoking prevalence by gender: An agent-based model.

    PubMed

    Chao, Dingding; Hashimoto, Hideki; Kondo, Naoki

    2015-12-01

    Smoking behavior is tightly related to socioeconomic status and gender, though the dynamic and non-linear association of smoking prevalence across socioeconomic status and gender groups has not been fully examined. With a special focus on gender-bound differences in the susceptibility to social influence of surrounding others' behaviors, we developed an agent-based model to explore how socioeconomic disparity between and within gender groups affects changes in smoking prevalence. Our developed base model reasonably reproduced the actual trend changes by gender groups over the past 5 years in Japan. Counterfactual experiments with the developed model revealed that closing within- and between-gender disparities in socioeconomic status had a limited impact on reducing smoking prevalence. To the contrary, greater socioeconomic disparity facilitated the reduction in prevalence among males, but it impeded that reduction in females. The counterfactual scenario with equalizing gender-bound susceptibility to social influence among women to men's level showed a dramatic reduction in female prevalence without changing the reduction in male prevalence. Simulation results may provide alternative explanation of the growing disparity in smoking prevalence despite improved welfare equality observed in many developed countries, and suggest that redistribution policies may have side effects of widening health gap. Instead, social policy to reduce social pressures to smoking and support interventions to enhance resilience to the pressure targeting the vulnerable population (in this study, women) would be a more effective strategy in combating the tobacco epidemic and closing the health gap.

  4. UAV Swarm Tactics: An Agent-Based Simulation and Markov Process Analysis

    DTIC Science & Technology

    2013-06-01

    NPS NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS UAV SWARM TACTICS: AN AGENT-BASED SIM ULATION AND MARKOV PROCESS ANALYSIS Thesis...inina; tho d ... _ . aod oompiotinl and ~_i .. tho roIloction of .. form. tion. Sond oommonu fQPrdina; thi!; burdon Mlim. m 0< a ny <>tho< ...,oct...TACTICS : AN AGENT-BASED SIMULATION AND MARKOV PROCESS ANALYSIS 1 So. " NUMBER ’. AU 1 Sd. PROJECT Uwe Gaertner 1 s.. TASK NUMBER 1 sr. WORK UNIT

  5. 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.

  6. Leveraging social influence to address overweight and obesity using agent-based models: the role of adolescent social networks.

    PubMed

    Zhang, J; Tong, L; Lamberson, P J; Durazo-Arvizu, R A; Luke, A; Shoham, D A

    2015-01-01

    The prevalence of adolescent overweight and obesity (hereafter, simply "overweight") in the US has increased over the past several decades. Individually-targeted prevention and treatment strategies targeting individuals have been disappointing, leading some to propose leveraging social networks to improve interventions. We hypothesized that social network dynamics (social marginalization; homophily on body mass index, BMI) and the strength of peer influence would increase or decrease the proportion of network member (agents) becoming overweight over a simulated year, and that peer influence would operate differently in social networks with greater overweight. We built an agent-based model (ABM) using results from R-SIENA. ABMs allow for the exploration of potential interventions using simulated agents. Initial model specifications were drawn from Wave 1 of the National Longitudinal Study of Adolescent Health (Add Health). We focused on a single saturation school with complete network and BMI data over two waves (n = 624). The model was validated against empirical observations at Wave 2. We focused on overall overweight prevalence after a simulated year. Five experiments were conducted: (1) changing attractiveness of high-BMI agents; (2) changing homophily on BMI; (3) changing the strength of peer influence; (4) shifting the overall BMI distribution; and (5) targeting dietary interventions to highly connected individuals. Increasing peer influence showed a dramatic decrease in the prevalence of overweight; making peer influence negative (i.e., doing the opposite of friends) increased overweight. However, the effect of peer influence varied based on the underlying distribution of BMI; when BMI was increased overall, stronger peer influence increased proportion of overweight. Other interventions, including targeted dieting, had little impact. Peer influence may be a viable target in overweight interventions, but the distribution of body size in the population needs to

  7. 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

  8. 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.

  9. 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.

  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. 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.

  12. 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

  13. Applying GIS and high performance agent-based simulation for managing an Old World Screwworm fly invasion of Australia.

    PubMed

    Welch, M C; Kwan, P W; Sajeev, A S M

    2014-10-01

    Agent-based modelling has proven to be a promising approach for developing rich simulations for complex phenomena that provide decision support functions across a broad range of areas including biological, social and agricultural sciences. This paper demonstrates how high performance computing technologies, namely General-Purpose Computing on Graphics Processing Units (GPGPU), and commercial Geographic Information Systems (GIS) can be applied to develop a national scale, agent-based simulation of an incursion of Old World Screwworm fly (OWS fly) into the Australian mainland. The development of this simulation model leverages the combination of massively data-parallel processing capabilities supported by NVidia's Compute Unified Device Architecture (CUDA) and the advanced spatial visualisation capabilities of GIS. These technologies have enabled the implementation of an individual-based, stochastic lifecycle and dispersal algorithm for the OWS fly invasion. The simulation model draws upon a wide range of biological data as input to stochastically determine the reproduction and survival of the OWS fly through the different stages of its lifecycle and dispersal of gravid females. Through this model, a highly efficient computational platform has been developed for studying the effectiveness of control and mitigation strategies and their associated economic impact on livestock industries can be materialised.

  14. 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

  15. 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.

  16. 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

  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. GridLAB-D: An Agent-Based Simulation Framework for Smart Grids

    DOE PAGES

    Chassin, David P.; Fuller, Jason C.; Djilali, Ned

    2014-01-01

    Simulation of smart grid technologies requires a fundamentally new approach to integrated modeling of power systems, energy markets, building technologies, and the plethora of other resources and assets that are becoming part of modern electricity production, delivery, and consumption systems. As a result, the US Department of Energy’s Office of Electricity commissioned the development of a new type of power system simulation tool called GridLAB-D that uses an agent-based approach to simulating smart grids. This paper presents the numerical methods and approach to time-series simulation used by GridLAB-D and reviews applications in power system studies, market design, building control systemmore » design, and integration of wind power in a smart grid.« less

  19. GridLAB-D: An Agent-Based Simulation Framework for Smart Grids

    SciTech Connect

    Chassin, David P.; Fuller, Jason C.; Djilali, Ned

    2014-06-23

    Simulation of smart grid technologies requires a fundamentally new approach to integrated modeling of power systems, energy markets, building technologies, and the plethora of other resources and assets that are becoming part of modern electricity production, delivery, and consumption systems. As a result, the US Department of Energy’s Office of Electricity commissioned the development of a new type of power system simulation tool called GridLAB-D that uses an agent-based approach to simulating smart grids. This paper presents the numerical methods and approach to time-series simulation used by GridLAB-D and reviews applications in power system studies, market design, building control system design, and integration of wind power in a smart grid.

  20. ModelforAnalyzing Human Communication Network Based onAgent-Based Simulation

    NASA Astrophysics Data System (ADS)

    Matsuyama, Shinako; Terano, Takao

    This paper discusses dynamic properties of human communications networks, which appears as a result of informationexchanges among people. We propose agent-based simulation (ABS) to examine implicit mechanisms behind the dynamics. The ABS enables us to reveal the characteristics and the differences of the networks regarding the specific communicationgroups. We perform experiments on the ABS with activity data from questionnaires survey and with virtual data which isdifferent from the activity data. We compare the difference between them and show the effectiveness of the ABS through theexperiments.

  1. 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.

  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. An Agent-Based Labor Market Simulation with Endogenous Skill-Demand

    NASA Astrophysics Data System (ADS)

    Gemkow, S.

    This paper considers an agent-based labor market simulation to examine the influence of skills on wages and unemployment rates. Therefore less and highly skilled workers as well as less and highly productive vacancies are implemented. The skill distribution is exogenous whereas the distribution of the less and highly productive vacancies is endogenous. The different opportunities of the skill groups on the labor market are established by skill requirements. This means that a highly productive vacancy can only be filled by a highly skilled unemployed. Different skill distributions, which can also be interpreted as skill-biased technological change, are simulated by incrementing the skill level of highly skilled persons exogenously. This simulation also provides a microeconomic foundation of the matching function often used in theoretical approaches.

  4. Security Analysis of Selected AMI Failure Scenarios Using Agent Based Game Theoretic Simulation

    SciTech Connect

    Abercrombie, Robert K; Schlicher, Bob G; Sheldon, Frederick T

    2014-01-01

    Information security analysis can be performed using game theory implemented in dynamic Agent Based Game Theoretic (ABGT) simulations. Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, and information assets. We concentrated our analysis on the Advanced Metering Infrastructure (AMI) functional domain which the National Electric Sector Cyber security Organization Resource (NESCOR) working group has currently documented 29 failure scenarios. The strategy for the game was developed by analyzing five electric sector representative failure scenarios contained in the AMI functional domain. From these five selected scenarios, we characterize them into three specific threat categories affecting confidentiality, integrity and availability (CIA). The analysis using our ABGT simulation demonstrates how to model the AMI functional domain using a set of rationalized game theoretic rules decomposed from the failure scenarios in terms of how those scenarios might impact the AMI network with respect to CIA.

  5. 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.

  6. 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

  7. A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact

    SciTech Connect

    Cui, Xiaohui; Liu, Cheng; Kim, Hoe Kyoung; Kao, Shih-Chieh; Tuttle, Mark A; Bhaduri, Budhendra L

    2011-01-01

    The variation of household attributes such as income, travel distance, age, household member, and education for different residential areas may generate different market penetration rates for plug-in hybrid electric vehicle (PHEV). Residential areas with higher PHEV ownership could increase peak electric demand locally and require utilities to upgrade the electric distribution infrastructure even though the capacity of the regional power grid is under-utilized. Estimating the future PHEV ownership distribution at the residential household level can help us understand the impact of PHEV fleet on power line congestion, transformer overload and other unforeseen problems at the local residential distribution network level. It can also help utilities manage the timing of recharging demand to maximize load factors and utilization of existing distribution resources. This paper presents a multi agent-based simulation framework for 1) modeling spatial distribution of PHEV ownership at local residential household level, 2) discovering PHEV hot zones where PHEV ownership may quickly increase in the near future, and 3) estimating the impacts of the increasing PHEV ownership on the local electric distribution network with different charging strategies. In this paper, we use Knox County, TN as a case study to show the simulation results of the agent-based model (ABM) framework. However, the framework can be easily applied to other local areas in the US.

  8. An Agent-Based Simulation for Investigating the Impact of Stereotypes on Task-Oriented Group Formation

    NASA Astrophysics Data System (ADS)

    Maghami, Mahsa; Sukthankar, Gita

    In this paper, we introduce an agent-based simulation for investigating the impact of social factors on the formation and evolution of task-oriented groups. Task-oriented groups are created explicitly to perform a task, and all members derive benefits from task completion. However, even in cases when all group members act in a way that is locally optimal for task completion, social forces that have mild effects on choice of associates can have a measurable impact on task completion performance. In this paper, we show how our simulation can be used to model the impact of stereotypes on group formation. In our simulation, stereotypes are based on observable features, learned from prior experience, and only affect an agent's link formation preferences. Even without assuming stereotypes affect the agents' willingness or ability to complete tasks, the long-term modifications that stereotypes have on the agents' social network impair the agents' ability to form groups with sufficient diversity of skills, as compared to agents who form links randomly. An interesting finding is that this effect holds even in cases where stereotype preference and skill existence are completely uncorrelated.

  9. Promoting Conceptual Change for Complex Systems Understanding: Outcomes of an Agent-Based Participatory Simulation

    NASA Astrophysics Data System (ADS)

    Rates, Christopher A.; Mulvey, Bridget K.; Feldon, David F.

    2016-08-01

    Components of complex systems apply across multiple subject areas, and teaching these components may help students build unifying conceptual links. Students, however, often have difficulty learning these components, and limited research exists to understand what types of interventions may best help improve understanding. We investigated 32 high school students' understandings of complex systems components and whether an agent-based simulation could improve their understandings. Pretest and posttest essays were coded for changes in six components to determine whether students showed more expert thinking about the complex system of the Chesapeake Bay watershed. Results showed significant improvement for the components Emergence ( r = .26, p = .03), Order ( r = .37, p = .002), and Tradeoffs ( r = .44, p = .001). Implications include that the experiential nature of the simulation has the potential to support conceptual change for some complex systems components, presenting a promising option for complex systems instruction.

  10. Automated multi-objective calibration of biological agent-based simulations.

    PubMed

    Read, Mark N; Alden, Kieran; Rose, Louis M; Timmis, Jon

    2016-09-01

    Computational agent-based simulation (ABS) is increasingly used to complement laboratory techniques in advancing our understanding of biological systems. Calibration, the identification of parameter values that align simulation with biological behaviours, becomes challenging as increasingly complex biological domains are simulated. Complex domains cannot be characterized by single metrics alone, rendering simulation calibration a fundamentally multi-metric optimization problem that typical calibration techniques cannot handle. Yet calibration is an essential activity in simulation-based science; the baseline calibration forms a control for subsequent experimentation and hence is fundamental in the interpretation of results. Here, we develop and showcase a method, built around multi-objective optimization, for calibrating ABSs against complex target behaviours requiring several metrics (termed objectives) to characterize. Multi-objective calibration (MOC) delivers those sets of parameter values representing optimal trade-offs in simulation performance against each metric, in the form of a Pareto front. We use MOC to calibrate a well-understood immunological simulation against both established a priori and previously unestablished target behaviours. Furthermore, we show that simulation-borne conclusions are broadly, but not entirely, robust to adopting baseline parameter values from different extremes of the Pareto front, highlighting the importance of MOC's identification of numerous calibration solutions. We devise a method for detecting overfitting in a multi-objective context, not previously possible, used to save computational effort by terminating MOC when no improved solutions will be found. MOC can significantly impact biological simulation, adding rigour to and speeding up an otherwise time-consuming calibration process and highlighting inappropriate biological capture by simulations that cannot be well calibrated. As such, it produces more accurate

  11. Agent-based modeling of the effects of social norms on enrollment in payments for ecosystem services.

    PubMed

    Chen, Xiaodong; Lupi, Frank; An, Li; Sheely, Ryan; Viña, Andrés; Liu, Jianguo

    2012-03-24

    Conservation investments are increasingly being implemented through payments for ecosystem services (PES) for the protection and restoration of ecosystem services around the world. Previous studies suggested that social norms have substantial impacts on environmental behaviors of humans, including enrollment of PES programs. However, it is still not well understood how social norms are affected by the design of PES programs and how the evolution of social norms may affect the efficiency of conservation investments. In this paper, we developed an agent-based simulation model to demonstrate the evolution and impacts of social norms on the enrollment of agricultural land in a PES program. We applied the model to land plots that have been enrolled in China's Grain-to-Green Program (GTGP) to examine reenrollment in an alternative payment program when the current payments ceased. The study was conducted in Wolong Nature Reserve where several thousand plant and animal species, including giant pandas, may benefit from the reenrollment. We found that over 15% more GTGP land can be reenrolled at the same payment if social norms were leveraged by allowing more than ten rounds of interactions among landholders regarding their reenrollment decisions. With only three rounds of interactions, an additional 7.5% GTGP land was reenrolled at the same payment due to the effects of social norms. In addition, the effects of social norms were largest at intermediate payments and were smaller at much higher or much smaller payments. Even in circumstances where frequent interactions among landholders about their enrollment decisions are not feasible, policy arrangements that divide households into multiple waves for sequential enrollment can enroll over 11% more land at a given payment level. The approach presented in this paper can be used to improve the efficiency of existing PES programs and many other conservation investments worldwide.

  12. 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.

  13. Agent-Based Crowd Simulation Considering Emotion Contagion for Emergency Evacuation Problem

    NASA Astrophysics Data System (ADS)

    Faroqi, H.; Mesgari, M.-S.

    2015-12-01

    During emergencies, emotions greatly affect human behaviour. For more realistic multi-agent systems in simulations of emergency evacuations, it is important to incorporate emotions and their effects on the agents. In few words, emotional contagion is a process in which a person or group influences the emotions or behavior of another person or group through the conscious or unconscious induction of emotion states and behavioral attitudes. In this study, we simulate an emergency situation in an open square area with three exits considering Adults and Children agents with different behavior. Also, Security agents are considered in order to guide Adults and Children for finding the exits and be calm. Six levels of emotion levels are considered for each agent in different scenarios and situations. The agent-based simulated model initialize with the random scattering of agent populations and then when an alarm occurs, each agent react to the situation based on its and neighbors current circumstances. The main goal of each agent is firstly to find the exit, and then help other agents to find their ways. Numbers of exited agents along with their emotion levels and damaged agents are compared in different scenarios with different initialization in order to evaluate the achieved results of the simulated model. NetLogo 5.2 is used as the multi-agent simulation framework with R language as the developing language.

  14. Changing crops in response to climate: virtual Nang Rong, Thailand in an agent based simulation.

    PubMed

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

    2014-09-01

    The effects of extended climatic variability on agricultural land use were explored for the type of system found in villages of northeastern Thailand. An agent based model developed for the Nang Rong district was used to simulate land allotted to jasmine rice, heavy rice, cassava, and sugar cane. The land use choices in the model depended on likely economic outcomes, but included elements of bounded rationality in dependence on household demography. The socioeconomic dynamics are endogenous in the system, and climate changes were added as exogenous drivers. Villages changed their agricultural effort in many different ways. Most villages reduced the amount of land under cultivation, primarily with reduction in jasmine rice, but others did not. The variation in responses to climate change indicates potential sensitivity to initial conditions and path dependence for this type of system. The differences between our virtual villages and the real villages of the region indicate effects of bounded rationality and limits on model applications.

  15. Agent-based simulation as a tool for the built environment.

    PubMed

    Gaudiano, Paolo

    2013-08-01

    There is a growing need to increase the performance of the built environment through a combination of improved design, retrofitting of existing structures, and behavioral and policy change. Increased performance includes decreasing construction and operational costs, improving efficiency, reducing energy consumption and overall carbon footprint, and increasing the health, safety, and comfort of building occupants. Data collection and analysis are central to ongoing efforts in performance improvement. The growth of sensor and monitoring technologies, coupled with the proliferation of building automation systems, is quickly leading to an explosion in the amount, quality, and format of building performance data. What is needed are methodologies for extracting viable information from these data and using the results to effect meaningful change. Furthermore, occupant behavior and attitudes must be taken into account. This paper summarizes agent-based simulation and describes its potential as an approach to support analysis, design, and performance improvements in the built environment.

  16. Changing crops in response to climate: virtual Nang Rong, Thailand in an agent based simulation

    PubMed Central

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

    2014-01-01

    The effects of extended climatic variability on agricultural land use were explored for the type of system found in villages of northeastern Thailand. An agent based model developed for the Nang Rong district was used to simulate land allotted to jasmine rice, heavy rice, cassava, and sugar cane. The land use choices in the model depended on likely economic outcomes, but included elements of bounded rationality in dependence on household demography. The socioeconomic dynamics are endogenous in the system, and climate changes were added as exogenous drivers. Villages changed their agricultural effort in many different ways. Most villages reduced the amount of land under cultivation, primarily with reduction in jasmine rice, but others did not. The variation in responses to climate change indicates potential sensitivity to initial conditions and path dependence for this type of system. The differences between our virtual villages and the real villages of the region indicate effects of bounded rationality and limits on model applications. PMID:25061240

  17. Method for distributed agent-based non-expert simulation of manufacturing process behavior

    DOEpatents

    Ivezic, Nenad; Potok, Thomas E.

    2004-11-30

    A method for distributed agent based non-expert simulation of manufacturing process behavior on a single-processor computer comprises the steps of: object modeling a manufacturing technique having a plurality of processes; associating a distributed agent with each the process; and, programming each the agent to respond to discrete events corresponding to the manufacturing technique, wherein each discrete event triggers a programmed response. The method can further comprise the step of transmitting the discrete events to each agent in a message loop. In addition, the programming step comprises the step of conditioning each agent to respond to a discrete event selected from the group consisting of a clock tick message, a resources received message, and a request for output production message.

  18. 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.

  19. 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.

  20. Design of a Mobile Agent-Based Adaptive Communication Middleware for Federations of Critical Infrastructure Simulations

    NASA Astrophysics Data System (ADS)

    Görbil, Gökçe; Gelenbe, Erol

    The simulation of critical infrastructures (CI) can involve the use of diverse domain specific simulators that run on geographically distant sites. These diverse simulators must then be coordinated to run concurrently in order to evaluate the performance of critical infrastructures which influence each other, especially in emergency or resource-critical situations. We therefore describe the design of an adaptive communication middleware that provides reliable and real-time one-to-one and group communications for federations of CI simulators over a wide-area network (WAN). The proposed middleware is composed of mobile agent-based peer-to-peer (P2P) overlays, called virtual networks (VNets), to enable resilient, adaptive and real-time communications over unreliable and dynamic physical networks (PNets). The autonomous software agents comprising the communication middleware monitor their performance and the underlying PNet, and dynamically adapt the P2P overlay and migrate over the PNet in order to optimize communications according to the requirements of the federation and the current conditions of the PNet. Reliable communications is provided via redundancy within the communication middleware and intelligent migration of agents over the PNet. The proposed middleware integrates security methods in order to protect the communication infrastructure against attacks and provide privacy and anonymity to the participants of the federation. Experiments with an initial version of the communication middleware over a real-life networking testbed show that promising improvements can be obtained for unicast and group communications via the agent migration capability of our middleware.

  1. Investigating the role of water in the Diffusion of Cholera using Agent-Based simulation

    NASA Astrophysics Data System (ADS)

    Augustijn, Ellen-Wien; Doldersum, Tom; Augustijn, Denie

    2014-05-01

    Traditionally, cholera was considered to be a waterborne disease. Currently we know that many other factors can contribute to the spread of this disease including human mobility and human behavior. However, the hydrological component in cholera diffusion is significant. The interplay between cholera and water includes bacteria (V. cholera) that survive in the aquatic environment, the possibility that run-off water from dumpsites carries the bacteria to surface water (rivers and lakes), and when the bacteria reach streams they can be carried downstream to infect new locations. Modelling is a very important tool to build theory on the interplay between different types of transmission mechanisms that together are responsible for the spread of Cholera. Agent-based simulation models are very suitable to incorporate behavior at individual level and to reproduce emergence. However, it is more difficult to incorporate the hydrological components in this type of model. In this research we present the hydrological component of an Agent-Based Cholera model developed to study a Cholera epidemic in Kumasi (Ghana) in 2005. The model was calibrated on the relative contribution of each community to the distributed pattern of cholera rather than the absolute number of incidences. Analysis of the results shows that water plays an important role in the diffusion of cholera: 75% of the cholera cases were infected via river water that was contaminated by runoff from the dumpsites. To initiate infections upstream, the probability of environment-to-human transmission seemed to be overestimated compared to what may be expected from literature. Scenario analyses show that there is a strong relation between the epidemic curve and the rainfall. Removing dumpsites that are situated close to the river resulted in a strong decrease in the number of cholera cases. Results are sensitive to the scheduling of the daily activities and the survival time of the cholera bacteria.

  2. 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

  3. 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.

  4. A Scaffolding Framework to Support Learning of Emergent Phenomena Using Multi-Agent-Based Simulation Environments

    NASA Astrophysics Data System (ADS)

    Basu, Satabdi; Sengupta, Pratim; Biswas, Gautam

    2015-04-01

    Students from middle school to college have difficulties in interpreting and understanding complex systems such as ecological phenomena. Researchers have suggested that students experience difficulties in reconciling the relationships between individuals, populations, and species, as well as the interactions between organisms and their environment in the ecosystem. Multi-agent-based computational models (MABMs) can explicitly capture agents and their interactions by representing individual actors as computational objects with assigned rules. As a result, the collective aggregate-level behavior of the population dynamically emerges from simulations that generate the aggregation of these interactions. Past studies have used a variety of scaffolds to help students learn ecological phenomena. Yet, there is no theoretical framework that supports the systematic design of scaffolds to aid students' learning in MABMs. Our paper addresses this issue by proposing a comprehensive framework for the design, analysis, and evaluation of scaffolding to support students' learning of ecology in a MABM. We present a study in which middle school students used a MABM to investigate and learn about a desert ecosystem. We identify the different types of scaffolds needed to support inquiry learning activities in this simulation environment and use our theoretical framework to demonstrate the effectiveness of our scaffolds in helping students develop a deep understanding of the complex ecological behaviors represented in the simulation..

  5. Agent-Based Spatiotemporal Simulation of Biomolecular Systems within the Open Source MASON Framework

    PubMed Central

    Pérez-Rodríguez, Gael; Pérez-Pérez, Martín; Glez-Peña, Daniel; Azevedo, Nuno F.; Lourenço, Anália

    2015-01-01

    Agent-based modelling is being used to represent biological systems with increasing frequency and success. This paper presents the implementation of a new tool for biomolecular reaction modelling in the open source Multiagent Simulator of Neighborhoods framework. The rationale behind this new tool is the necessity to describe interactions at the molecular level to be able to grasp emergent and meaningful biological behaviour. We are particularly interested in characterising and quantifying the various effects that facilitate biocatalysis. Enzymes may display high specificity for their substrates and this information is crucial to the engineering and optimisation of bioprocesses. Simulation results demonstrate that molecule distributions, reaction rate parameters, and structural parameters can be adjusted separately in the simulation allowing a comprehensive study of individual effects in the context of realistic cell environments. While higher percentage of collisions with occurrence of reaction increases the affinity of the enzyme to the substrate, a faster reaction (i.e., turnover number) leads to a smaller number of time steps. Slower diffusion rates and molecular crowding (physical hurdles) decrease the collision rate of reactants, hence reducing the reaction rate, as expected. Also, the random distribution of molecules affects the results significantly. PMID:25874228

  6. Evaluation of wholesale electric power market rules and financial risk management by agent-based simulations

    NASA Astrophysics Data System (ADS)

    Yu, Nanpeng

    As U.S. regional electricity markets continue to refine their market structures, designs and rules of operation in various ways, two critical issues are emerging. First, although much experience has been gained and costly and valuable lessons have been learned, there is still a lack of a systematic platform for evaluation of the impact of a new market design from both engineering and economic points of view. Second, the transition from a monopoly paradigm characterized by a guaranteed rate of return to a competitive market created various unfamiliar financial risks for various market participants, especially for the Investor Owned Utilities (IOUs) and Independent Power Producers (IPPs). This dissertation uses agent-based simulation methods to tackle the market rules evaluation and financial risk management problems. The California energy crisis in 2000-01 showed what could happen to an electricity market if it did not go through a comprehensive and rigorous testing before its implementation. Due to the complexity of the market structure, strategic interaction between the participants, and the underlying physics, it is difficult to fully evaluate the implications of potential changes to market rules. This dissertation presents a flexible and integrative method to assess market designs through agent-based simulations. Realistic simulation scenarios on a 225-bus system are constructed for evaluation of the proposed PJM-like market power mitigation rules of the California electricity market. Simulation results show that in the absence of market power mitigation, generation company (GenCo) agents facilitated by Q-learning are able to exploit the market flaws and make significantly higher profits relative to the competitive benchmark. The incorporation of PJM-like local market power mitigation rules is shown to be effective in suppressing the exercise of market power. The importance of financial risk management is exemplified by the recent financial crisis. In this

  7. An agent-based simulation of extirpation of Ceratitis capitata applied to invasions in California.

    PubMed

    Manoukis, Nicholas C; Hoffman, Kevin

    2014-01-01

    We present an agent-based simulation (ABS) of Ceratitis capitata ("Medfly") developed for estimating the time to extirpation of this pest in areas where quarantines and eradication treatments were immediately imposed. We use the ABS, implemented in the program MED-FOES, to study seven different outbreaks that occurred in Southern California from 2008 to 2010. Results are compared with the length of intervention and quarantine imposed by the State, based on a linear developmental model (thermal unit accumulation, or "degree-day"). MED-FOES is a useful tool for invasive species managers as it incorporates more information from the known biology of the Medfly, and includes the important feature of being demographically explicit, providing significant improvements over simple degree-day calculations. While there was general agreement between the length of quarantine by degree-day and the time to extirpation indicated by MED-FOES, the ABS suggests that the margin of safety varies among cases and that in two cases the quarantine may have been excessively long. We also examined changes in the number of individuals over time in MED-FOES and conducted a sensitivity analysis for one of the outbreaks to explore the role of various input parameters on simulation outcomes. While our implementation of the ABS in this work is motivated by C. capitata and takes extirpation as a postulate, the simulation is very flexible and can be used to study a variety of questions on the invasion biology of pest insects and methods proposed to manage or eradicate such species.

  8. Semantic Agent-Based Service Middleware and Simulation for Smart Cities.

    PubMed

    Liu, Ming; Xu, Yang; Hu, Haixiao; Mohammed, Abdul-Wahid

    2016-12-21

    With the development of Machine-to-Machine (M2M) technology, a variety of embedded and mobile devices is integrated to interact via the platform of the Internet of Things, especially in the domain of smart cities. One of the primary challenges is that selecting the appropriate services or service combination for upper layer applications is hard, which is due to the absence of a unified semantical service description pattern, as well as the service selection mechanism. In this paper, we define a semantic service representation model from four key properties: Capability (C), Deployment (D), Resource (R) and IOData (IO). Based on this model, an agent-based middleware is built to support semantic service enablement. In this middleware, we present an efficient semantic service discovery and matching approach for a service combination process, which calculates the semantic similarity between services, and a heuristic algorithm to search the service candidates for a specific service request. Based on this design, we propose a simulation of virtual urban fire fighting, and the experimental results manifest the feasibility and efficiency of our design.

  9. Semantic Agent-Based Service Middleware and Simulation for Smart Cities

    PubMed Central

    Liu, Ming; Xu, Yang; Hu, Haixiao; Mohammed, Abdul-Wahid

    2016-01-01

    With the development of Machine-to-Machine (M2M) technology, a variety of embedded and mobile devices is integrated to interact via the platform of the Internet of Things, especially in the domain of smart cities. One of the primary challenges is that selecting the appropriate services or service combination for upper layer applications is hard, which is due to the absence of a unified semantical service description pattern, as well as the service selection mechanism. In this paper, we define a semantic service representation model from four key properties: Capability (C), Deployment (D), Resource (R) and IOData (IO). Based on this model, an agent-based middleware is built to support semantic service enablement. In this middleware, we present an efficient semantic service discovery and matching approach for a service combination process, which calculates the semantic similarity between services, and a heuristic algorithm to search the service candidates for a specific service request. Based on this design, we propose a simulation of virtual urban fire fighting, and the experimental results manifest the feasibility and efficiency of our design. PMID:28009818

  10. 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

  11. Biophysically realistic filament bending dynamics in agent-based biological simulation.

    PubMed

    Alberts, Jonathan B

    2009-01-01

    An appealing tool for study of the complex biological behaviors that can emerge from networks of simple molecular interactions is an agent-based, computational simulation that explicitly tracks small-scale local interactions--following thousands to millions of states through time. For many critical cell processes (e.g. cytokinetic furrow specification, nuclear centration, cytokinesis), the flexible nature of cytoskeletal filaments is likely to be critical. Any computer model that hopes to explain the complex emergent behaviors in these processes therefore needs to encode filament flexibility in a realistic manner. Here I present a numerically convenient and biophysically realistic method for modeling cytoskeletal filament flexibility in silico. Each cytoskeletal filament is represented by a series of rigid segments linked end-to-end in series with a variable attachment point for the translational elastic element. This connection scheme allows an empirically tuning, for a wide range of segment sizes, viscosities, and time-steps, that endows any filament species with the experimentally observed (or theoretically expected) static force deflection, relaxation time-constant, and thermal writhing motions. I additionally employ a unique pair of elastic elements--one representing the axial and the other the bending rigidity- that formulate the restoring force in terms of single time-step constraint resolution. This method is highly local -adjacent rigid segments of a filament only interact with one another through constraint forces-and is thus well-suited to simulations in which arbitrary additional forces (e.g. those representing interactions of a filament with other bodies or cross-links / entanglements between filaments) may be present. Implementation in code is straightforward; Java source code is available at www.celldynamics.org.

  12. 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

  13. Agent-based evacuation simulation for spatial allocation assessment of urban shelters

    NASA Astrophysics Data System (ADS)

    Yu, Jia; Wen, Jiahong; Jiang, Yong

    2015-12-01

    The construction of urban shelters is one of the most important work in urban planning and disaster prevention. The spatial allocation assessment is a fundamental pre-step for spatial location-allocation of urban shelters. This paper introduces a new method which makes use of agent-based technology to implement evacuation simulation so as to conduct dynamic spatial allocation assessment of urban shelters. The method can not only accomplish traditional geospatial evaluation for urban shelters, but also simulate the evacuation process of the residents to shelters. The advantage of utilizing this method lies into three aspects: (1) the evacuation time of each citizen from a residential building to the shelter can be estimated more reasonably; (2) the total evacuation time of all the residents in a region is able to be obtained; (3) the road congestions in evacuation in sheltering can be detected so as to take precautionary measures to prevent potential risks. In this study, three types of agents are designed: shelter agents, government agents and resident agents. Shelter agents select specified land uses as shelter candidates for different disasters. Government agents delimitate the service area of each shelter, in other words, regulate which shelter a person should take, in accordance with the administrative boundaries and road distance between the person's position and the location of the shelter. Resident agents have a series of attributes, such as ages, positions, walking speeds, and so on. They also have several behaviors, such as reducing speed when walking in the crowd, helping old people and children, and so on. Integrating these three types of agents which are correlated with each other, evacuation procedures can be simulated and dynamic allocation assessment of shelters will be achieved. A case study in Jing'an District, Shanghai, China, was conducted to demonstrate the feasibility of the method. A scenario of earthquake disaster which occurs in nighttime

  14. Autonomous Agent-Based Simulation of a Model Simulating the Human Air-Threat Assessment Process

    DTIC Science & Technology

    2004-03-01

    multi - agent system (MAS) technology and is implemented in Java programming language. This research is a portion of Red Intent Project whose goal is to ultimately implement a model to predict the intent of any given track in the environment. For any air track in the simulation, two sets of agents are created, one for controlling track actions and one for predicting its identity and intent based on information received from track, the geopolitical situation and intelligence. The simulation is also capable of identifying coordinated actions between air tracks. We

  15. 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

  16. 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.

  17. Towards a conceptual multi-agent-based framework to simulate the spatial group decision-making process

    NASA Astrophysics Data System (ADS)

    Ghavami, Seyed Morsal; Taleai, Mohammad

    2017-04-01

    Most spatial problems are multi-actor, multi-issue and multi-phase in nature. In addition to their intrinsic complexity, spatial problems usually involve groups of actors from different organizational and cognitive backgrounds, all of whom participate in a social structure to resolve or reduce the complexity of a given problem. Hence, it is important to study and evaluate what different aspects influence the spatial problem resolution process. Recently, multi-agent systems consisting of groups of separate agent entities all interacting with each other have been put forward as appropriate tools to use to study and resolve such problems. In this study, then in order to generate a better level of understanding regarding the spatial problem group decision-making process, a conceptual multi-agent-based framework is used that represents and specifies all the necessary concepts and entities needed to aid group decision making, based on a simulation of the group decision-making process as well as the relationships that exist among the different concepts involved. The study uses five main influencing entities as concepts in the simulation process: spatial influence, individual-level influence, group-level influence, negotiation influence and group performance measures. Further, it explains the relationship among different concepts in a descriptive rather than explanatory manner. To illustrate the proposed framework, the approval process for an urban land use master plan in Zanjan—a provincial capital in Iran—is simulated using MAS, the results highlighting the effectiveness of applying an MAS-based framework when wishing to study the group decision-making process used to resolve spatial problems.

  18. Towards a conceptual multi-agent-based framework to simulate the spatial group decision-making process

    NASA Astrophysics Data System (ADS)

    Ghavami, Seyed Morsal; Taleai, Mohammad

    2016-11-01

    Most spatial problems are multi-actor, multi-issue and multi-phase in nature. In addition to their intrinsic complexity, spatial problems usually involve groups of actors from different organizational and cognitive backgrounds, all of whom participate in a social structure to resolve or reduce the complexity of a given problem. Hence, it is important to study and evaluate what different aspects influence the spatial problem resolution process. Recently, multi-agent systems consisting of groups of separate agent entities all interacting with each other have been put forward as appropriate tools to use to study and resolve such problems. In this study, then in order to generate a better level of understanding regarding the spatial problem group decision-making process, a conceptual multi-agent-based framework is used that represents and specifies all the necessary concepts and entities needed to aid group decision making, based on a simulation of the group decision-making process as well as the relationships that exist among the different concepts involved. The study uses five main influencing entities as concepts in the simulation process: spatial influence, individual-level influence, group-level influence, negotiation influence and group performance measures. Further, it explains the relationship among different concepts in a descriptive rather than explanatory manner. To illustrate the proposed framework, the approval process for an urban land use master plan in Zanjan—a provincial capital in Iran—is simulated using MAS, the results highlighting the effectiveness of applying an MAS-based framework when wishing to study the group decision-making process used to resolve spatial problems.

  19. 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.

  20. Proposal of Classification Method of Time Series Data in International Emissions Trading Market Using Agent-based Simulation

    NASA Astrophysics Data System (ADS)

    Nakada, Tomohiro; Takadama, Keiki; Watanabe, Shigeyoshi

    This paper proposes the classification method using Bayesian analytical method to classify the time series data in the international emissions trading market depend on the agent-based simulation and compares the case with Discrete Fourier transform analytical method. The purpose demonstrates the analytical methods mapping time series data such as market price. These analytical methods have revealed the following results: (1) the classification methods indicate the distance of mapping from the time series data, it is easier the understanding and inference than time series data; (2) these methods can analyze the uncertain time series data using the distance via agent-based simulation including stationary process and non-stationary process; and (3) Bayesian analytical method can show the 1% difference description of the emission reduction targets of agent.

  1. How Crime Spreads Through Imitation in Social Networks: A Simulation Model

    NASA Astrophysics Data System (ADS)

    Punzo, Valentina

    In this chapter an agent-based model for investigating how crime spreads through social networks is presented. Some theoretical issues related to the sociological explanation of crime are tested through simulation. The agent-based simulation allows us to investigate the relative impact of some mechanisms of social influence on crime, within a set of controlled simulated experiments.

  2. 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

  3. On-lattice agent-based simulation of populations of cells within the open-source Chaste framework.

    PubMed

    Figueredo, Grazziela P; Joshi, Tanvi V; Osborne, James M; Byrne, Helen M; Owen, Markus R

    2013-04-06

    Over the years, agent-based models have been developed that combine cell division and reinforced random walks of cells on a regular lattice, reaction-diffusion equations for nutrients and growth factors; and ordinary differential equations for the subcellular networks regulating the cell cycle. When linked to a vascular layer, this multiple scale model framework has been applied to tumour growth and therapy. Here, we report on the creation of an agent-based multi-scale environment amalgamating the characteristics of these models within a Virtual Physiological Human (VPH) Exemplar Project. This project enables reuse, integration, expansion and sharing of the model and relevant data. The agent-based and reaction-diffusion parts of the multi-scale model have been implemented and are available for download as part of the latest public release of Chaste (Cancer, Heart and Soft Tissue Environment; http://www.cs.ox.ac.uk/chaste/), part of the VPH Toolkit (http://toolkit.vph-noe.eu/). The environment functionalities are verified against the original models, in addition to extra validation of all aspects of the code. In this work, we present the details of the implementation of the agent-based environment, including the system description, the conceptual model, the development of the simulation model and the processes of verification and validation of the simulation results. We explore the potential use of the environment by presenting exemplar applications of the 'what if' scenarios that can easily be studied in the environment. These examples relate to tumour growth, cellular competition for resources and tumour responses to hypoxia (low oxygen levels). We conclude our work by summarizing the future steps for the expansion of the current system.

  4. Multi-Agent Based Simulation of Optimal Urban Land Use Allocation in the Middle Reaches of the Yangtze River, China

    NASA Astrophysics Data System (ADS)

    Zeng, Y.; Huang, W.; Jin, W.; Li, S.

    2016-06-01

    The optimization of land-use allocation is one of important approaches to achieve regional sustainable development. This study selects Chang-Zhu-Tan agglomeration as study area and proposed a new land use optimization allocation model. Using multi-agent based simulation model, the future urban land use optimization allocation was simulated in 2020 and 2030 under three different scenarios. This kind of quantitative information about urban land use optimization allocation and urban expansions in future would be of great interest to urban planning, water and land resource management, and climate change research.

  5. Using the Integration of Discrete Event and Agent-Based Simulation to Enhance Outpatient Service Quality in an Orthopedic Department

    PubMed Central

    Kittipittayakorn, Cholada

    2016-01-01

    Many hospitals are currently paying more attention to patient satisfaction since it is an important service quality index. Many Asian countries' healthcare systems have a mixed-type registration, accepting both walk-in patients and scheduled patients. This complex registration system causes a long patient waiting time in outpatient clinics. Different approaches have been proposed to reduce the waiting time. This study uses the integration of discrete event simulation (DES) and agent-based simulation (ABS) to improve patient waiting time and is the first attempt to apply this approach to solve this key problem faced by orthopedic departments. From the data collected, patient behaviors are modeled and incorporated into a massive agent-based simulation. The proposed approach is an aid for analyzing and modifying orthopedic department processes, allows us to consider far more details, and provides more reliable results. After applying the proposed approach, the total waiting time of the orthopedic department fell from 1246.39 minutes to 847.21 minutes. Thus, using the correct simulation model significantly reduces patient waiting time in an orthopedic department. PMID:27195606

  6. 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.

  7. 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

  8. Can human-like Bots control collective mood: agent-based simulations of online chats

    NASA Astrophysics Data System (ADS)

    Tadić, Bosiljka; Šuvakov, Milovan

    2013-10-01

    Using an agent-based modeling approach, in this paper, we study self-organized dynamics of interacting agents in the presence of chat Bots. Different Bots with tunable ‘human-like’ attributes, which exchange emotional messages with agents, are considered, and the collective emotional behavior of agents is quantitatively analyzed. In particular, using detrended fractal analysis we determine persistent fluctuations and temporal correlations in time series of agent activity and statistics of avalanches carrying emotional messages of agents when Bots favoring positive/negative affects are active. We determine the impact of Bots and identify parameters that can modulate that impact. Our analysis suggests that, by these measures, the emotional Bots induce collective emotion among interacting agents by suitably altering the fractal characteristics of the underlying stochastic process. Positive emotion Bots are slightly more effective than negative emotion Bots. Moreover, Bots which periodically alternate between positive and negative emotion can enhance fluctuations in the system, leading to avalanches of agent messages that are reminiscent of self-organized critical states.

  9. [Research on multi-agent based modeling and simulation of hospital system].

    PubMed

    Zhao, Junping; Yang, Hongqiao; Guo, Huayuan; Li, Yi; Zhang, Zhenjiang; Li, Shuzhang

    2010-12-01

    In this paper, the theory of complex adaptive system (CAS) and its modeling method are introduced. The complex characters of the hospital system is analyzed. The agile manufacturing and cell reconstruction technologies are used to reconstruct the hospital system. Then we set forth a research for simulation of hospital system based on the methodology of Multi-Agent technology and high level architecture (HLA). Finally, a simulation framework based on HLA for hospital system is presented.

  10. 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

  11. Agent Based Modeling and Simulation Framework for Supply Chain Risk Management

    DTIC Science & Technology

    2012-03-01

    timed Petri net based simulation (Tuncel and Alpan 2010), and Monte Carlo (White 1995, Wu and Olson 2008, and Schmitt and Singh 2009). More detail...benefit costs. (Li and Li 2008) 26 Chen, Zhou, and Hu propose an agent-oriented Petri net model for an inventory- scheduling model, with focus on the...problems of analysis and modeling of multi-agent systems. Petri net aims at researching the organization structure and dynamic behavior of a system

  12. Agent-Based Simulations of Malaria Transmissions with Applications to a Study Site in Thailand

    NASA Technical Reports Server (NTRS)

    Kiang, Richard K.; Adimi, Farida; Zollner, Gabriela E.; Coleman, Russell E.

    2006-01-01

    The dynamics of malaria transmission are driven by environmental, biotic and socioeconomic factors. Because of the geographic dependency of these factors and the complex interactions among them, it is difficult to generalize the key factors that perpetuate or intensify malaria transmission. Methods: Discrete event simulations were used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. Meteorological and environmental parameters may be derived from satellite data. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results were compared with mosquito vector and human malaria data acquired over 4.5 years (June 1999 - January 2004) in Kong Mong Tha, a remote village in Kanchanaburi Province, western Thailand. Results: Three years of transmissions of vivax and falciparum malaria were simulated for a hypothetical hamlet with approximately 1/7 of the study site population. The model generated results for a number of scenarios, including applications of larvicide and insecticide, asymptomatic cases receiving or not receiving treatment, blocking malaria transmission in mosquito vectors, and increasing the density of farm (host) animals in the hamlet. Transmission characteristics and trends in the simulated results are comparable to actual data collected at the study site.

  13. Bee++: An Object-Oriented, Agent-Based Simulator for Honey Bee Colonies.

    PubMed

    Betti, Matthew; LeClair, Josh; Wahl, Lindi M; Zamir, Mair

    2017-03-10

    We present a model and associated simulation package (www.beeplusplus.ca) to capture the natural dynamics of a honey bee colony in a spatially-explicit landscape, with temporally-variable, weather-dependent parameters. The simulation tracks bees of different ages and castes, food stores within the colony, pollen and nectar sources and the spatial position of individual foragers outside the hive. We track explicitly the intake of pesticides in individual bees and their ability to metabolize these toxins, such that the impact of sub-lethal doses of pesticides can be explored. Moreover, pathogen populations (in particular, Nosema apis, Nosema cerenae and Varroa mites) have been included in the model and may be introduced at any time or location. The ability to study interactions among pesticides, climate, biodiversity and pathogens in this predictive framework should prove useful to a wide range of researchers studying honey bee populations. To this end, the simulation package is written in open source, object-oriented code (C++) and can be easily modified by the user. Here, we demonstrate the use of the model by exploring the effects of sub-lethal pesticide exposure on the flight behaviour of foragers.

  14. Bee++: An Object-Oriented, Agent-Based Simulator for Honey Bee Colonies

    PubMed Central

    Betti, Matthew; LeClair, Josh; Wahl, Lindi M.; Zamir, Mair

    2017-01-01

    We present a model and associated simulation package (www.beeplusplus.ca) to capture the natural dynamics of a honey bee colony in a spatially-explicit landscape, with temporally-variable, weather-dependent parameters. The simulation tracks bees of different ages and castes, food stores within the colony, pollen and nectar sources and the spatial position of individual foragers outside the hive. We track explicitly the intake of pesticides in individual bees and their ability to metabolize these toxins, such that the impact of sub-lethal doses of pesticides can be explored. Moreover, pathogen populations (in particular, Nosema apis, Nosema cerenae and Varroa mites) have been included in the model and may be introduced at any time or location. The ability to study interactions among pesticides, climate, biodiversity and pathogens in this predictive framework should prove useful to a wide range of researchers studying honey bee populations. To this end, the simulation package is written in open source, object-oriented code (C++) and can be easily modified by the user. Here, we demonstrate the use of the model by exploring the effects of sub-lethal pesticide exposure on the flight behaviour of foragers. PMID:28287445

  15. The contribution of agent-based simulations to conservation management on a Natura 2000 site.

    PubMed

    Dupont, Hélène; Gourmelon, Françoise; Rouan, Mathias; Le Viol, Isabelle; Kerbiriou, Christian

    2016-03-01

    The conservation of biodiversity today must include the participation and support of local stakeholders. Natura 2000 can be considered as a conservation system that, in its application in most EU countries, relies on the participation of local stakeholders. Our study proposes a scientific method for participatory modelling, with the aim of contributing to the conservation management of habitats and species at a Natura 2000 site (Crozon Peninsula, Bretagne, France) that is representative of in landuse changes in coastal areas. We make use of companion modelling and its associated tools (scenario-planning, GIS, multi-agent modelling and simulations) to consider possible futures through the co-construction of management scenarios and the understanding of their consequences on different indicators of biodiversity status (habitats, avifauna, flora). The maintenance of human activities as they have been carried out since the creation of the Natura 2000s zone allows the biodiversity values to remain stable. Extensive agricultural activities have been shown to be essential to this maintenance, whereas management sustained by the multiplication of conservation actions brings about variable results according to the indicators. None of the scenarios has a positive incidence on the set of indicators. However, an understanding of the modelling system and the results of the simulations allow for the refining of the selection of conservation actions in relation to the species to be preserved.

  16. Evolutionary Agent-Based Simulation of the Introduction of New Technologies in Air Traffic Management

    NASA Technical Reports Server (NTRS)

    Yliniemi, Logan; Agogino, Adrian K.; Tumer, Kagan

    2014-01-01

    Accurate simulation of the effects of integrating new technologies into a complex system is critical to the modernization of our antiquated air traffic system, where there exist many layers of interacting procedures, controls, and automation all designed to cooperate with human operators. Additions of even simple new technologies may result in unexpected emergent behavior due to complex human/ machine interactions. One approach is to create high-fidelity human models coming from the field of human factors that can simulate a rich set of behaviors. However, such models are difficult to produce, especially to show unexpected emergent behavior coming from many human operators interacting simultaneously within a complex system. Instead of engineering complex human models, we directly model the emergent behavior by evolving goal directed agents, representing human users. Using evolution we can predict how the agent representing the human user reacts given his/her goals. In this paradigm, each autonomous agent in a system pursues individual goals, and the behavior of the system emerges from the interactions, foreseen or unforeseen, between the agents/actors. We show that this method reflects the integration of new technologies in a historical case, and apply the same methodology for a possible future technology.

  17. ActivitySim: large-scale agent based activity generation for infrastructure simulation

    SciTech Connect

    Gali, Emmanuel; Eidenbenz, Stephan; Mniszewski, Sue; Cuellar, Leticia; Teuscher, Christof

    2008-01-01

    The United States' Department of Homeland Security aims to model, simulate, and analyze critical infrastructure and their interdependencies across multiple sectors such as electric power, telecommunications, water distribution, transportation, etc. We introduce ActivitySim, an activity simulator for a population of millions of individual agents each characterized by a set of demographic attributes that is based on US census data. ActivitySim generates daily schedules for each agent that consists of a sequence of activities, such as sleeping, shopping, working etc., each being scheduled at a geographic location, such as businesses or private residences that is appropriate for the activity type and for the personal situation of the agent. ActivitySim has been developed as part of a larger effort to understand the interdependencies among national infrastructure networks and their demand profiles that emerge from the different activities of individuals in baseline scenarios as well as emergency scenarios, such as hurricane evacuations. We present the scalable software engineering principles underlying ActivitySim, the socia-technical modeling paradigms that drive the activity generation, and proof-of-principle results for a scenario in the Twin Cities, MN area of 2.6 M agents.

  18. Simulated trust: a cheap social learning strategy.

    PubMed

    Vanderelst, Dieter; Ahn, René M C; Barakova, Emilia I

    2009-11-01

    Animals use heuristic strategies to determine from which conspecifics to learn socially. This leads to directed social learning. Directed social learning protects them from copying non-adaptive information. So far, the strategies of animals, leading to directed social learning, are assumed to rely on (possibly indirect) inferences about the demonstrator's success. As an alternative to this assumption, we propose a strategy that only uses self-established estimates of the pay-offs of behavior. We evaluate the strategy in a number of agent-based simulations. Critically, the strategy's success is warranted by the inclusion of an incremental learning mechanism. Our findings point out new theoretical opportunities to regulate social learning for animals. More broadly, our simulations emphasize the need to include a realistic learning mechanism in game-theoretic studies of social learning strategies, and call for re-evaluation of previous findings.

  19. 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

  20. An agent-based simulation model of patient choice of health care providers in accountable care organizations.

    PubMed

    Alibrahim, Abdullah; Wu, Shinyi

    2016-10-04

    Accountable care organizations (ACO) in the United States show promise in controlling health care costs while preserving patients' choice of providers. Understanding the effects of patient choice is critical in novel payment and delivery models like ACO that depend on continuity of care and accountability. The financial, utilization, and behavioral implications associated with a patient's decision to forego local health care providers for more distant ones to access higher quality care remain unknown. To study this question, we used an agent-based simulation model of a health care market composed of providers able to form ACO serving patients and embedded it in a conditional logit decision model to examine patients capable of choosing their care providers. This simulation focuses on Medicare beneficiaries and their congestive heart failure (CHF) outcomes. We place the patient agents in an ACO delivery system model in which provider agents decide if they remain in an ACO and perform a quality improving CHF disease management intervention. Illustrative results show that allowing patients to choose their providers reduces the yearly payment per CHF patient by $320, reduces mortality rates by 0.12 percentage points and hospitalization rates by 0.44 percentage points, and marginally increases provider participation in ACO. This study demonstrates a model capable of quantifying the effects of patient choice in a theoretical ACO system and provides a potential tool for policymakers to understand implications of patient choice and assess potential policy controls.

  1. Agent-based modeling to simulate contamination events and evaluate threat management strategies in water distribution systems.

    PubMed

    Zechman, Emily M

    2011-05-01

    In the event of contamination of a water distribution system, decisions must be made to mitigate the impact of the contamination and to protect public health. Making threat management decisions while a contaminant spreads through the network is a dynamic and interactive process. Response actions taken by the utility managers and water consumption choices made by the consumers will affect the hydraulics, and thus the spread of the contaminant plume, in the network. A modeling framework that allows the simulation of a contamination event under the effects of actions taken by utility managers and consumers will be a useful tool for the analysis of alternative threat mitigation and management strategies. This article presents a multiagent modeling framework that combines agent-based, mechanistic, and dynamic methods. Agents select actions based on a set of rules that represent an individual's autonomy, goal-based desires, and reaction to the environment and the actions of other agents. Consumer behaviors including ingestion, mobility, reduction of water demands, and word-of-mouth communication are simulated. Management strategies are evaluated, including opening hydrants to flush the contaminant and broadcasts. As actions taken by consumer agents and utility operators affect demands and flows in the system, the mechanistic model is updated. Management strategies are evaluated based on the exposure of the population to the contaminant. The framework is designed to consider the typical issues involved in water distribution threat management and provides valuable analysis of threat containment strategies for water distribution system contamination events.

  2. Agent-based Modeling to Simulate the Diffusion of Water-Efficient Innovations and the Emergence of Urban Water Sustainability

    NASA Astrophysics Data System (ADS)

    Kanta, L.; Giacomoni, M.; Shafiee, M. E.; Berglund, E.

    2014-12-01

    The sustainability of water resources is threatened by urbanization, as increasing demands deplete water availability, and changes to the landscape alter runoff and the flow regime of receiving water bodies. Utility managers typically manage urban water resources through the use of centralized solutions, such as large reservoirs, which may be limited in their ability balance the needs of urbanization and ecological systems. Decentralized technologies, on the other hand, may improve the health of the water resources system and deliver urban water services. For example, low impact development technologies, such as rainwater harvesting, and water-efficient technologies, such as low-flow faucets and toilets, may be adopted by households to retain rainwater and reduce demands, offsetting the need for new centralized infrastructure. Decentralized technologies may create new complexities in infrastructure and water management, as decentralization depends on community behavior and participation beyond traditional water resources planning. Messages about water shortages and water quality from peers and the water utility managers can influence the adoption of new technologies. As a result, feedbacks between consumers and water resources emerge, creating a complex system. This research develops a framework to simulate the diffusion of water-efficient innovations and the sustainability of urban water resources, by coupling models of households in a community, hydrologic models of a water resources system, and a cellular automata model of land use change. Agent-based models are developed to simulate the land use and water demand decisions of individual households, and behavioral rules are encoded to simulate communication with other agents and adoption of decentralized technologies, using a model of the diffusion of innovation. The framework is applied for an illustrative case study to simulate water resources sustainability over a long-term planning horizon.

  3. Rural-urban migration including formal and informal workers in the urban sector: an agent-based numerical simulation study

    NASA Astrophysics Data System (ADS)

    Branco, Nilton; Oliveira, Tharnier; Silveira, Jaylson

    2012-02-01

    The goal of this work is to study rural-urban migration in the early stages of industrialization. We use an agent-based model and take into account the existence of informal and formal workers on the urban sector and possible migration movements, dependent on the agents' social and private utilities. Our agents are place on vertices of a square lattice, such that each vertex has only one agent. Rural, urban informal and urban formal workers are represented by different states of a three-state Ising model. At every step, a fraction a of the agents may change sectors or migrate. The total utility of a given agent is then calculated and compared to a random utility, in order to check if this agent turns into an actual migrant or changes sector. The dynamics is carried out until an equilibrium state is reached and equilibrium variables are then calculated and compared to available data. We find that a generalized Harris-Todaro condition is satisfied [1] on these equilibrium regimes, i.e, the ratio between expected wages between any pair of sectors reach a constant value. [4pt] [1] J. J. Silveira, A. L. Esp'indola and T. J. Penna, Physica A, 364, 445 (2006).

  4. An agent-based model to simulate tsetse fly distribution and control techniques: a case study in Nguruman, Kenya

    PubMed Central

    Lin, Shengpan; DeVisser, Mark H.; Messina, Joseph P.

    2015-01-01

    Background African trypanosomiasis, also known as “sleeping sickness” in humans and “nagana” in livestock is an important vector-borne disease in Sub-Saharan Africa. Control of trypanosomiasis has focused on eliminating the vector, the tsetse fly (Glossina, spp.). Effective tsetse fly control planning requires models to predict tsetse population and distribution changes over time and space. Traditional planning models have used statistical tools to predict tsetse distributions and have been hindered by limited field survey data. Methodology/Results We developed an Agent-Based Model (ABM) to provide timing and location information for tsetse fly control without presence/absence training data. The model is driven by daily remotely-sensed environment data. The model provides a flexible tool linking environmental changes with individual biology to analyze tsetse control methods such as aerial insecticide spraying, wild animal control, releasing irradiated sterile tsetse males, and land use and cover modification. Significance This is a bottom-up process-based model with freely available data as inputs that can be easily transferred to a new area. The tsetse population simulation more closely approximates real conditions than those using traditional statistical models making it a useful tool in tsetse fly control planning. PMID:26309347

  5. Multiobjective Decision Making Policies and Coordination Mechanisms in Hierarchical Organizations: Results of an Agent-Based Simulation

    PubMed Central

    2014-01-01

    This paper analyses how different coordination modes and different multiobjective decision making approaches interfere with each other in hierarchical organizations. The investigation is based on an agent-based simulation. We apply a modified NK-model in which we map multiobjective decision making as adaptive walk on multiple performance landscapes, whereby each landscape represents one objective. We find that the impact of the coordination mode on the performance and the speed of performance improvement is critically affected by the selected multiobjective decision making approach. In certain setups, the performances achieved with the more complex multiobjective decision making approaches turn out to be less sensitive to the coordination mode than the performances achieved with the less complex multiobjective decision making approaches. Furthermore, we present results on the impact of the nature of interactions among decisions on the achieved performance in multiobjective setups. Our results give guidance on how to control the performance contribution of objectives to overall performance and answer the question how effective certain multiobjective decision making approaches perform under certain circumstances (coordination mode and interdependencies among decisions). PMID:25152926

  6. Agent based simulation on the process of human flesh search-From perspective of knowledge and emotion

    NASA Astrophysics Data System (ADS)

    Zhu, Hou; Hu, Bin

    2017-03-01

    Human flesh search as a new net crowed behavior, on the one hand can help us to find some special information, on the other hand may lead to privacy leaking and offending human right. In order to study the mechanism of human flesh search, this paper proposes a simulation model based on agent-based model and complex networks. The computational experiments show some useful results. Discovered information quantity and involved personal ratio are highly correlated, and most of net citizens will take part in the human flesh search or will not take part in the human flesh search. Knowledge quantity does not influence involved personal ratio, but influences whether HFS can find out the target human. When the knowledge concentrates on hub nodes, the discovered information quantity is either perfect or almost zero. Emotion of net citizens influences both discovered information quantity and involved personal ratio. Concretely, when net citizens are calm to face the search topic, it will be hardly to find out the target; But when net citizens are agitated, the target will be found out easily.

  7. Modeling the 2014 Ebola Virus Epidemic - Agent-Based Simulations, Temporal Analysis and Future Predictions for Liberia and Sierra Leone.

    PubMed

    Siettos, Constantinos; Anastassopoulou, Cleo; Russo, Lucia; Grigoras, Christos; Mylonakis, Eleftherios

    2015-03-09

    We developed an agent-based model to investigate the epidemic dynamics of Ebola virus disease (EVD) in Liberia and Sierra Leone from May 27 to December 21, 2014. The dynamics of the agent-based simulator evolve on small-world transmission networks of sizes equal to the population of each country, with adjustable densities to account for the effects of public health intervention policies and individual behavioral responses to the evolving epidemic. Based on time series of the official case counts from the World Health Organization (WHO), we provide estimates for key epidemiological variables by employing the so-called Equation-Free approach. The underlying transmission networks were characterized by rather random structures in the two countries with densities decreasing by ~19% from the early (May 27-early August) to the last period (mid October-December 21). Our estimates for the values of key epidemiological variables, such as the mean time to death, recovery and the case fatality rate, are very close to the ones reported by the WHO Ebola response team during the early period of the epidemic (until September 14) that were calculated based on clinical data. Specifically, regarding the effective reproductive number Re, our analysis suggests that until mid October, Re was above 2.3 in both countries; from mid October to December 21, Re dropped well below unity in Liberia, indicating a saturation of the epidemic, while in Sierra Leone it was around 1.9, indicating an ongoing epidemic. Accordingly, a ten-week projection from December 21 estimated that the epidemic will fade out in Liberia in early March; in contrast, our results flashed a note of caution for Sierra Leone since the cumulative number of cases could reach as high as 18,000, and the number of deaths might exceed 5,000, by early March 2015. However, by processing the reported data of the very last period (December 21, 2014-January 18, 2015), we obtained more optimistic estimates indicative of a remission of

  8. Understanding coupled natural and human systems on fire prone landscapes: integrating wildfire simulation into an agent based planning system.

    NASA Astrophysics Data System (ADS)

    Barros, Ana; Ager, Alan; Preisler, Haiganoush; Day, Michelle; Spies, Tom; Bolte, John

    2015-04-01

    Agent-based models (ABM) allow users to examine the long-term effects of agent decisions in complex systems where multiple agents and processes interact. This framework has potential application to study the dynamics of coupled natural and human systems where multiple stimuli determine trajectories over both space and time. We used Envision, a landscape based ABM, to analyze long-term wildfire dynamics in a heterogeneous, multi-owner landscape in Oregon, USA. Landscape dynamics are affected by land management policies, actors decisions, and autonomous processes such as vegetation succession, wildfire, or at a broader scale, climate change. Key questions include: 1) How are landscape dynamics influenced by policies and institutions, and 2) How do land management policies and actor decisions interact to produce intended and unintended consequences with respect to wildfire on fire-prone landscapes. Applying Envision to address these questions required the development of a wildfire module that could accurately simulate wildfires on the heterogeneous landscapes within the study area in terms of replicating historical fire size distribution, spatial distribution and fire intensity. In this paper we describe the development and testing of a mechanistic fire simulation system within Envision and application of the model on a 3.2 million fire prone landscape in central Oregon USA. The core fire spread equations use the Minimum Travel Time algorithm developed by M Finney. The model operates on a daily time step and uses a fire prediction system based on the relationship between energy release component and historical fires. Specifically, daily wildfire probabilities and sizes are generated from statistical analyses of historical fires in relation to daily ERC values. The MTT was coupled with the vegetation dynamics module in Envision to allow communication between the respective subsystem and effectively model fire effects and vegetation dynamics after a wildfire. Canopy and

  9. Modelling Temporal Schedule of Urban Trains Using Agent-Based Simulation and NSGA2-BASED Multiobjective Optimization Approaches

    NASA Astrophysics Data System (ADS)

    Sahelgozin, M.; Alimohammadi, A.

    2015-12-01

    Increasing distances between locations of residence and services leads to a large number of daily commutes in urban areas. Developing subway systems has been taken into consideration of transportation managers as a response to this huge amount of travel demands. In developments of subway infrastructures, representing a temporal schedule for trains is an important task; because an appropriately designed timetable decreases Total passenger travel times, Total Operation Costs and Energy Consumption of trains. Since these variables are not positively correlated, subway scheduling is considered as a multi-criteria optimization problem. Therefore, proposing a proper solution for subway scheduling has been always a controversial issue. On the other hand, research on a phenomenon requires a summarized representation of the real world that is known as Model. In this study, it is attempted to model temporal schedule of urban trains that can be applied in Multi-Criteria Subway Schedule Optimization (MCSSO) problems. At first, a conceptual framework is represented for MCSSO. Then, an agent-based simulation environment is implemented to perform Sensitivity Analysis (SA) that is used to extract the interrelations between the framework components. These interrelations is then taken into account in order to construct the proposed model. In order to evaluate performance of the model in MCSSO problems, Tehran subway line no. 1 is considered as the case study. Results of the study show that the model was able to generate an acceptable distribution of Pareto-optimal solutions which are applicable in the real situations while solving a MCSSO is the goal. Also, the accuracy of the model in representing the operation of subway systems was significant.

  10. Simulating the time series of a selected gene expression profile in an agent-based tumor model

    NASA Astrophysics Data System (ADS)

    Mansury, Yuri; Deisboeck, Thomas S.

    2004-09-01

    To elucidate the role of environmental conditions in molecular-level dynamics and to study their impact on macroscopic brain tumor growth patterns, the expression of the genes Tenascin C and PCNA in a 2D agent-based model for the migratory trait is calibrated using experimental data from the literature, while the expression of these genes for the proliferative trait is obtained as the model output. Numerical results confirm that the gene expression of Tenascin C is indeed consistently higher in the migratory glioma cell phenotype and show that the expression of PCNA is consistently higher among proliferating tumor cells. Intriguingly, the time series of the tumor cells’ gene expression exhibit a sudden change in behavior during the invasion of the tumor into a nutrient-abundant region, showing a robust positive correlation between the expression of Tenascin C and the tumor’s diameter, yet a strong negative correlation between the expression of PCNA and the diameter. These molecular-level dynamics correspond to the emergence of a structural asymmetry in the form of a bulging tumor rim in the nutrient-abundant region. The simulated time series thus supports the critical role of the migratory cell phenotype during both the tumor system’s overall macroscopic expansion and the evolvement of regional growth patterns, particularly in the later stages. Furthermore, detrended fluctuation analysis (DFA) suggests that for prediction purposes, the simulated gene expression profiles of Tenascin C and PCNA that were determined separately for the migrating and proliferating phenotypes exhibit lesser predictability than those of the phenotypic mixture combining all viable tumor cells typically found in clinical biopsies. Finally, partitioning the tumor into distinct geographic regions of interest (ROI) reveals that the gene expression profile of tumor cells in the quadrant close to the nutrient-abundant region is representative for the entire tumor whereas the expression

  11. 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

  12. Integrating the simulation of domestic water demand behaviour to an urban water model using agent based modelling

    NASA Astrophysics Data System (ADS)

    Koutiva, Ifigeneia; Makropoulos, Christos

    2015-04-01

    The urban water system's sustainable evolution requires tools that can analyse and simulate the complete cycle including both physical and cultural environments. One of the main challenges, in this regard, is the design and development of tools that are able to simulate the society's water demand behaviour and the way policy measures affect it. The effects of these policy measures are a function of personal opinions that subsequently lead to the formation of people's attitudes. These attitudes will eventually form behaviours. This work presents the design of an ABM tool for addressing the social dimension of the urban water system. The created tool, called Urban Water Agents' Behaviour (UWAB) model, was implemented, using the NetLogo agent programming language. The main aim of the UWAB model is to capture the effects of policies and environmental pressures to water conservation behaviour of urban households. The model consists of agents representing urban households that are linked to each other creating a social network that influences the water conservation behaviour of its members. Household agents are influenced as well by policies and environmental pressures, such as drought. The UWAB model simulates behaviour resulting in the evolution of water conservation within an urban population. The final outcome of the model is the evolution of the distribution of different conservation levels (no, low, high) to the selected urban population. In addition, UWAB is implemented in combination with an existing urban water management simulation tool, the Urban Water Optioneering Tool (UWOT) in order to create a modelling platform aiming to facilitate an adaptive approach of water resources management. For the purposes of this proposed modelling platform, UWOT is used in a twofold manner: (1) to simulate domestic water demand evolution and (2) to simulate the response of the water system to the domestic water demand evolution. The main advantage of the UWAB - UWOT model

  13. 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

  14. Results and Lessons Learned from a Coupled Social and Physical Hydrology Model: Testing Alternative Water Management Policies and Institutional Structures Using Agent-Based Modeling and Regional Hydrology

    NASA Astrophysics Data System (ADS)

    Murphy, J.; Lammers, R. B.; Prousevitch, A.; Ozik, J.; Altaweel, M.; Collier, N. T.; Kliskey, A. D.; Alessa, L.

    2015-12-01

    Water Management in the U.S. Southwest is under increasing scrutiny as many areas endure persistent drought. The impact of these prolonged dry conditions is a product of regional climate and hydrological conditions, but also of a highly engineered water management infrastructure and a complex web of social arrangements whereby water is allocated, shared, exchanged, used, re-used, and finally consumed. We coupled an agent-based model with a regional hydrological model to understand the dynamics in one richly studied and highly populous area: southern Arizona, U.S.A., including metropolitan Phoenix and Tucson. There, multiple management entities representing an array of municipalities and other water providers and customers, including private companies and Native American tribes are enmeshed in a complex legal and economic context in which water is bought, leased, banked, and exchanged in a variety of ways and on multiple temporal and physical scales. A recurrent question in the literature of adaptive management is the impact of management structure on overall system performance. To explore this, we constructed an agent-based model to capture this social complexity, and coupled this with a physical hydrological model that we used to drive the system under a variety of water stress scenarios and to assess the regional impact of the social system's performance. We report the outcomes of ensembles of runs in which varieties of alternative policy constraints and management strategies are considered. We hope to contribute to policy discussions in this area and connected and legislatively similar areas (such as California) as current conditions change and existing legal and policy structures are revised. Additionally, we comment on the challenges of integrating models that ostensibly are in different domains (physical and social) but that independently represent a system in which physical processes and human actions are closely intertwined and difficult to disentangle.

  15. 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.

  16. 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.

  17. Understanding Islamist political violence through computational social simulation

    SciTech Connect

    Watkins, Jennifer H; Mackerrow, Edward P; Patelli, Paolo G; Eberhardt, Ariane; Stradling, Seth G

    2008-01-01

    Understanding the process that enables political violence is of great value in reducing the future demand for and support of violent opposition groups. Methods are needed that allow alternative scenarios and counterfactuals to be scientifically researched. Computational social simulation shows promise in developing 'computer experiments' that would be unfeasible or unethical in the real world. Additionally, the process of modeling and simulation reveals and challenges assumptions that may not be noted in theories, exposes areas where data is not available, and provides a rigorous, repeatable, and transparent framework for analyzing the complex dynamics of political violence. This paper demonstrates the computational modeling process using two simulation techniques: system dynamics and agent-based modeling. The benefits and drawbacks of both techniques are discussed. In developing these social simulations, we discovered that the social science concepts and theories needed to accurately simulate the associated psychological and social phenomena were lacking.

  18. Autonomous Agent-Based Simulation of an AEGIS Cruiser Combat Information Center Performing Battle Group Air Defense Commander Operations

    DTIC Science & Technology

    2003-03-01

    objects from O. • Operations with the task of representing the application of these operations and the reaction of the world to this attempt at... clickable ) (4) Simulation Interface: Tactical Display Contact Icons. • Contact Attributes (specific to the contact) 52 (5...Icon (6) Simulation Interface: CIC Agent Display • CIC Agent Icons ( clickable ) • CIC Equipment Icons ( clickable ) (7) Simulation Interface

  19. Ideal free distribution or dynamic game? An agent-based simulation study of trawling strategies with varying information

    NASA Astrophysics Data System (ADS)

    Beecham, J. A.; Engelhard, G. H.

    2007-10-01

    An ecological economic model of trawling is presented to demonstrate the effect of trawling location choice strategy on net input (rate of economic gain of fish caught per time spent less costs). Fishing location choice is considered to be a dynamic process whereby trawlers chose from among a repertoire of plastic strategies that they modify if their gains fall below a fixed proportion of the mean gains of the fleet as a whole. The distribution of fishing across different areas of a fishery follows an approximate ideal free distribution (IFD) with varying noise due to uncertainty. The least-productive areas are not utilised because initial net input never reaches the mean yield of better areas subject to competitive exploitation. In cases, where there is a weak temporal autocorrelation between fish stocks in a specific location, a plastic strategy of local translocation between trawls mixed with longer-range translocation increases realised input. The trawler can change its translocation strategy in the light of information about recent trawling success compared to its long-term average but, in contrast to predictions of the Marginal Value Theorem (MVT) model, does not know for certain what it will find by moving, so may need to sample new patches. The combination of the two types of translocation mirrored beam-trawling strategies used by the Dutch fleet and the resultant distribution of trawling effort is confirmed by analysis of historical effort distribution of British otter trawling fleets in the North Sea. Fisheries exploitation represents an area where dynamic agent-based adaptive models may be a better representation of the economic dynamics of a fleet than classically inspired optimisation models.

  20. Experimental Evaluation of Suitability of Selected Multi-Criteria Decision-Making Methods for Large-Scale Agent-Based Simulations

    PubMed Central

    2016-01-01

    Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the–server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models. PMID:27806061

  1. Autonomous-Agent Based Simulation of Anti- Submarine Warfare Operations with the Goal of Protecting a High Value Unit

    DTIC Science & Technology

    2004-03-01

    Multi Agent System (MAS) technique. The simulation interface is a Horizontal Display Center (HDC) which is very similar to a MEKQ2OO class Frigate Combat Information Center’s (CIC) HDC. The program uses Extensible Markup Language (XML) files for reading data for program scenarios; parameters are initialized before each run time begins. The simulation also provides all the output data at the end of run time for analysis purposes. The program user’s goal, and the purpose of the program, is to decrease the number of successful attacks against surface

  2. Real-Time Agent-Based Modeling Simulation with in-situ Visualization of Complex Biological Systems: A Case Study on Vocal Fold Inflammation and Healing.

    PubMed

    Seekhao, Nuttiiya; Shung, Caroline; JaJa, Joseph; Mongeau, Luc; Li-Jessen, Nicole Y K

    2016-05-01

    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.

  3. A framework for the use of agent based modeling to simulate inter- and intraindividual variation in human behaviors

    EPA Science Inventory

    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 ag...

  4. EPOCHS: A Platform for Agent-Based Electric Power and Communication Simulation Built from Commercial Off-The-Shelf Components

    DTIC Science & Technology

    2005-04-01

    to simplify the development of EMTDC scenarios. PSCAD is produced by the Manitoba HVDC Research Centre [25]. EMTDC simulates power scenarios in...Manitoba HVDC Research Centre, PSCAD/EMTDC Manual Getting Started. Winnipeg, Manitoba, Canada, 1998. [26] General Electric, "PSLF Manual," vol. 2003

  5. Development Approaches Coupled with Verification and Validation Methodologies for Agent-Based Mission-Level Analytical Combat Simulations

    DTIC Science & Technology

    2004-03-01

    Where Computers Meet Biology, Vintage Books, a division of Random House, Inc.: New York NY. 117. Liu, Bing, Siew-Hwee Choo , Shee-Ling Lok, Sing-Meng...Simpkins, Scott D., Eugene P. Paulo, , and Lyn R. Whitaker (2001) “Case Study in Modeling and Simulation Validation Methodology”. Proceedings of

  6. An Agent-Based Model of Private Woodland Owner Management Behavior Using Social Interactions, Information Flow, and Peer-To-Peer Networks.

    PubMed

    Huff, Emily Silver; Leahy, Jessica E; Hiebeler, David; Weiskittel, Aaron R; Noblet, Caroline L

    2015-01-01

    Privately owned woodlands are an important source of timber and ecosystem services in North America and worldwide. Impacts of management on these ecosystems and timber supply from these woodlands are difficult to estimate because complex behavioral theory informs the owner's management decisions. The decision-making environment consists of exogenous market factors, internal cognitive processes, and social interactions with fellow landowners, foresters, and other rural community members. This study seeks to understand how social interactions, information flow, and peer-to-peer networks influence timber harvesting behavior using an agent-based model. This theoretical model includes forested polygons in various states of 'harvest readiness' and three types of agents: forest landowners, foresters, and peer leaders (individuals trained in conservation who use peer-to-peer networking). Agent rules, interactions, and characteristics were parameterized with values from existing literature and an empirical survey of forest landowner attitudes, intentions, and demographics. The model demonstrates that as trust in foresters and peer leaders increases, the percentage of the forest that is harvested sustainably increases. Furthermore, peer leaders can serve to increase landowner trust in foresters. Model output and equations will inform forest policy and extension/outreach efforts. The model also serves as an important testing ground for new theories of landowner decision making and behavior.

  7. An Agent-Based Model of Private Woodland Owner Management Behavior Using Social Interactions, Information Flow, and Peer-To-Peer Networks

    PubMed Central

    Huff, Emily Silver; Leahy, Jessica E.; Hiebeler, David; Weiskittel, Aaron R.; Noblet, Caroline L.

    2015-01-01

    Privately owned woodlands are an important source of timber and ecosystem services in North America and worldwide. Impacts of management on these ecosystems and timber supply from these woodlands are difficult to estimate because complex behavioral theory informs the owner’s management decisions. The decision-making environment consists of exogenous market factors, internal cognitive processes, and social interactions with fellow landowners, foresters, and other rural community members. This study seeks to understand how social interactions, information flow, and peer-to-peer networks influence timber harvesting behavior using an agent-based model. This theoretical model includes forested polygons in various states of ‘harvest readiness’ and three types of agents: forest landowners, foresters, and peer leaders (individuals trained in conservation who use peer-to-peer networking). Agent rules, interactions, and characteristics were parameterized with values from existing literature and an empirical survey of forest landowner attitudes, intentions, and demographics. The model demonstrates that as trust in foresters and peer leaders increases, the percentage of the forest that is harvested sustainably increases. Furthermore, peer leaders can serve to increase landowner trust in foresters. Model output and equations will inform forest policy and extension/outreach efforts. The model also serves as an important testing ground for new theories of landowner decision making and behavior. PMID:26562429

  8. Incorporating fault tolerance in distributed agent based systems by simulating bio-computing model of stress pathways

    NASA Astrophysics Data System (ADS)

    Bansal, Arvind K.

    2006-05-01

    Bio-computing model of 'Distributed Multiple Intelligent Agents Systems' (BDMIAS) models agents as genes, a cooperating group of agents as operons - commonly regulated groups of genes, and the complex task as a set of interacting pathways such that the pathways involve multiple cooperating operons. The agents (or groups of agents) interact with each other using message passing and pattern based bindings that may reconfigure agent's function temporarily. In this paper, a technique has been described for incorporating fault tolerance in BDMIAS. The scheme is based upon simulating BDMIAS, exploiting the modeling of biological stress pathways, integration of fault avoidance, and distributed fault recovery of the crashed agents. Stress pathways are latent pathways in biological system that gets triggered very quickly, regulate the complex biological system by temporarily regulating or inactivating the undesirable pathways, and are essential to avoid catastrophic failures. Pattern based interaction between messages and agents allow multiple agents to react concurrently in response to single condition change represented by a message broadcast. The fault avoidance exploits the integration of the intelligent processing rate control using message based loop feedback and temporary reconfiguration that alters the data flow between functional modules within an agent, and may alter. The fault recovery exploits the concept of semi passive shadow agents - one on the local machine and other on the remote machine, dynamic polling of machines, logically time stamped messages to avoid message losses, and distributed archiving of volatile part of agent state on distributed machines. Various algorithms have been described.

  9. Agent Based Computing Machine

    DTIC Science & Technology

    2005-12-09

    coordinates as in cellular automata systems. But using biology as a model suggests that the most general systems must provide for partial, but constrained...17. SECURITY CLASSIFICATION OF 118. SECURITY CLASSIFICATION OF 19. SECURITY CLASSIFICATION OF 20. LIMITATION OF ABSTRA REPORT THIS PAGE ABSTRACT...system called an "agent based computing" machine (ABC Machine). The ABC Machine is motivated by cellular biochemistry and it is based upon a concept

  10. Use of an agent-based simulation model to evaluate a mobile-based system for supporting emergency evacuation decision making.

    PubMed

    Tian, Yu; Zhou, Tian-Shu; Yao, Qin; Zhang, Mao; Li, Jing-Song

    2014-12-01

    Recently, mass casualty incidents (MCIs) have been occurring frequently and have gained international attention. There is an urgent need for scientifically proven and effective emergency responses to MCIs, particularly as the severity of incidents is continuously increasing. The emergency response to MCIs is a multi-dimensional and multi-participant dynamic process that changes in real-time. The evacuation decisions that assign casualties to different hospitals in a region are very important and impact both the results of emergency treatment and the efficiency of medical resource utilization. Previously, decisions related to casualty evacuation were made by an incident commander with emergency experience and in accordance with macro emergency guidelines. There are few decision-supporting tools available to reduce the difficulty and psychological pressure associated with the evacuation decisions an incident commander must make. In this study, we have designed a mobile-based system to collect medical and temporal data produced during an emergency response to an MCI. Using this information, our system's decision-making model can provide personal evacuation suggestions that improve the overall outcome of an emergency response. The effectiveness of our system in reducing overall mortality has been validated by an agent-based simulation model established to simulate an emergency response to an MCI.

  11. Development of a three-dimensional multiscale agent-based tumor model: simulating gene-protein interaction profiles, cell phenotypes and multicellular patterns in brain cancer.

    PubMed

    Zhang, Le; Athale, Chaitanya A; Deisboeck, Thomas S

    2007-01-07

    Experimental evidence suggests that epidermal growth factor receptor (EGFR)-mediated activation of the signaling protein phospholipase Cgamma plays a critical role in a cancer cell's phenotypic decision to either proliferate or to migrate at a given point in time. Here, we present a novel three-dimensional multiscale agent-based model to simulate this cellular decision process in the context of a virtual brain tumor. Each tumor cell is equipped with an EGFR gene-protein interaction network module that also connects to a simplified cell cycle description. The simulation results show that over time proliferative and migratory cell populations not only oscillate but also directly impact the spatio-temporal expansion patterns of the entire cancer system. The percentage change in the concentration of the sub-cellular interaction network's molecular components fluctuates, and, for the 'proliferation-to-migration' switch we find that the phenotype triggering molecular profile to some degree varies as the tumor system grows and the microenvironment changes. We discuss potential implications of these findings for experimental and clinical cancer research.

  12. 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

  13. 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.

  14. Estimation of the age-specific per-contact probability of Ebola virus transmission in Liberia using agent-based simulations

    NASA Astrophysics Data System (ADS)

    Siettos, Constantinos I.; Anastassopoulou, Cleo; Russo, Lucia; Grigoras, Christos; Mylonakis, Eleftherios

    2016-06-01

    Based on multiscale agent-based computations we estimated the per-contact probability of transmission by age of the Ebola virus disease (EVD) that swept through Liberia from May 2014 to March 2015. For the approximation of the epidemic dynamics we have developed a detailed agent-based model with small-world interactions between individuals categorized by age. For the estimation of the structure of the evolving contact network as well as the per-contact transmission probabilities by age group we exploited the so called Equation-Free framework. Model parameters were fitted to official case counts reported by the World Health Organization (WHO) as well as to recently published data of key epidemiological variables, such as the mean time to death, recovery and the case fatality rate.

  15. An Agent-Based Cockpit Task Management System

    NASA Technical Reports Server (NTRS)

    Funk, Ken

    1997-01-01

    An agent-based program to facilitate Cockpit Task Management (CTM) in commercial transport aircraft is developed and evaluated. The agent-based program called the AgendaManager (AMgr) is described and evaluated in a part-task simulator study using airline pilots.

  16. 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.

  17. 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.

  18. 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

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

    DTIC Science & Technology

    2013-09-30

    for understanding and analyzing human behavior in a civil violence paradigm. This model employed two types of agents: an agent that can become...cognitions and behaviors. Unlike previous agent-based models of civil violence , this work includes the use of a hidden Markov process for simulating...these models can portray real insurgent environments. Keywords simulation · agent based model · insurgency · civil violence · graphics processing

  20. 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.

  1. Representing Trust in Cognitive Social Simulations

    NASA Astrophysics Data System (ADS)

    Pollock, Shawn S.; Alt, Jonathan K.; Darken, Christian J.

    Trust plays a critical role in communications, strength of relationships, and information processing at the individual and group level. Cognitive social simulations show promise in providing an experimental platform for the examination of social phenomena such as trust formation. This paper describes the initial attempts at representation of trust in a cognitive social simulation using reinforcement learning algorithms centered around a cooperative Public Commodity game within a dynamic social network.

  2. Study of photo-oxidative reactivity of sunscreening agents based on photo-oxidation of uric acid by kinetic Monte Carlo simulation.

    PubMed

    Moradmand Jalali, Hamed; Bashiri, Hadis; Rasa, Hossein

    2015-05-01

    In the present study, the mechanism of free radical production by light-reflective agents in sunscreens (TiO2, ZnO and ZrO2) was obtained by applying kinetic Monte Carlo simulation. The values of the rate constants for each step of the suggested mechanism have been obtained by simulation. The effect of the initial concentration of mineral oxides and uric acid on the rate of uric acid photo-oxidation by irradiation of some sun care agents has been studied. The kinetic Monte Carlo simulation results agree qualitatively with the existing experimental data for the production of free radicals by sun care agents.

  3. Agent-based forward analysis

    SciTech Connect

    Kerekes, Ryan A.; Jiao, Yu; Shankar, Mallikarjun; Potok, Thomas E.; Lusk, Rick M.

    2008-01-01

    We propose software agent-based "forward analysis" for efficient information retrieval in a network of sensing devices. In our approach, processing is pushed to the data at the edge of the network via intelligent software agents rather than pulling data to a central facility for processing. The agents are deployed with a specific query and perform varying levels of analysis of the data, communicating with each other and sending only relevant information back across the network. We demonstrate our concept in the context of face recognition using a wireless test bed comprised of PDA cell phones and laptops. We show that agent-based forward analysis can provide a significant increase in retrieval speed while decreasing bandwidth usage and information overload at the central facility. n

  4. 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.

  5. Social Identity Simulation System (SISTEM)

    DTIC Science & Technology

    2014-03-31

    number of people G = identity group (e.g. gender, ethnicity, etc.) D = identity (e.g. male/ female , White/Black/Spanish/… etc.) R = real resources for an...actions as part of a collective. The collective actions are driven by social identity entrepreneurs (SIDs) (Haslam & Reicher, 2007; Lal, 1997). These...social identity entrepreneurs only advocate a collective action on behalf of the group when they perceive benefits of advocating being greater than

  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. Development of an Agent-Based Model (ABM) to Simulate the Immune System and Integration of a Regression Method to Estimate the Key ABM Parameters by Fitting the Experimental Data.

    PubMed

    Tong, Xuming; Chen, Jinghang; Miao, Hongyu; Li, Tingting; Zhang, Le

    2015-01-01

    Agent-based models (ABM) and differential equations (DE) are two commonly used methods for immune system simulation. However, it is difficult for ABM to estimate key parameters of the model by incorporating experimental data, whereas the differential equation model is incapable of describing the complicated immune system in detail. To overcome these problems, we developed an integrated ABM regression model (IABMR). It can combine the advantages of ABM and DE by employing ABM to mimic the multi-scale immune system with various phenotypes and types of cells as well as using the input and output of ABM to build up the Loess regression for key parameter estimation. Next, we employed the greedy algorithm to estimate the key parameters of the ABM with respect to the same experimental data set and used ABM to describe a 3D immune system similar to previous studies that employed the DE model. These results indicate that IABMR not only has the potential to simulate the immune system at various scales, phenotypes and cell types, but can also accurately infer the key parameters like DE model. Therefore, this study innovatively developed a complex system development mechanism that could simulate the complicated immune system in detail like ABM and validate the reliability and efficiency of model like DE by fitting the experimental data.

  8. Development of an Agent-Based Model (ABM) to Simulate the Immune System and Integration of a Regression Method to Estimate the Key ABM Parameters by Fitting the Experimental Data

    PubMed Central

    Tong, Xuming; Chen, Jinghang; Miao, Hongyu; Li, Tingting; Zhang, Le

    2015-01-01

    Agent-based models (ABM) and differential equations (DE) are two commonly used methods for immune system simulation. However, it is difficult for ABM to estimate key parameters of the model by incorporating experimental data, whereas the differential equation model is incapable of describing the complicated immune system in detail. To overcome these problems, we developed an integrated ABM regression model (IABMR). It can combine the advantages of ABM and DE by employing ABM to mimic the multi-scale immune system with various phenotypes and types of cells as well as using the input and output of ABM to build up the Loess regression for key parameter estimation. Next, we employed the greedy algorithm to estimate the key parameters of the ABM with respect to the same experimental data set and used ABM to describe a 3D immune system similar to previous studies that employed the DE model. These results indicate that IABMR not only has the potential to simulate the immune system at various scales, phenotypes and cell types, but can also accurately infer the key parameters like DE model. Therefore, this study innovatively developed a complex system development mechanism that could simulate the complicated immune system in detail like ABM and validate the reliability and efficiency of model like DE by fitting the experimental data. PMID:26535589

  9. Agent Frameworks for Discrete Event Social Simulations

    DTIC Science & Technology

    2010-03-01

    of a general modeling approach to social simulation that embeds a multi - agent system within a DES framework, and propose several reusable agent... agent system to simulate changes in the beliefs, values, and interests (BVIs) of large social groups (Alt, Jackson, Hudak, & Steven Lieberman, 2010...to events from A. 2.3 Cultural Geography Model The Cultural Geography (CG) Model is an implementation of a DESS that uses an embedded multi

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. Fiction: Simulation of Social Worlds.

    PubMed

    Oatley, Keith

    2016-06-23

    Fiction is the simulation of selves in interaction. People who read it improve their understanding of others. This effect is especially marked with literary fiction, which also enables people to change themselves. These effects are due partly to the process of engagement in stories, which includes making inferences and becoming emotionally involved, and partly to the contents of fiction, which include complex characters and circumstances that we might not encounter in daily life. Fiction can be thought of as a form of consciousness of selves and others that can be passed from an author to a reader or spectator, and can be internalized to augment everyday cognition.

  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. Finding shared decisions in stakeholder networks: An agent-based approach

    NASA Astrophysics Data System (ADS)

    Le Pira, Michela; Inturri, Giuseppe; Ignaccolo, Matteo; Pluchino, Alessandro; Rapisarda, Andrea

    2017-01-01

    We address the problem of a participatory decision-making process where a shared priority list of alternatives has to be obtained while avoiding inconsistent decisions. An agent-based model (ABM) is proposed to mimic this process in different social networks of stakeholders who interact according to an opinion dynamics model. Simulations' results show the efficacy of interaction in finding a transitive and, above all, shared decision. These findings are in agreement with real participation experiences regarding transport planning decisions and can give useful suggestions on how to plan an effective participation process for sustainable policy-making based on opinion consensus.

  17. Information-Theoretic Approaches for Evaluating Complex Adaptive Social Simulation Systems

    SciTech Connect

    Omitaomu, Olufemi A; Ganguly, Auroop R; Jiao, Yu

    2009-01-01

    In this paper, we propose information-theoretic approaches for comparing and evaluating complex agent-based models. In information theoretic terms, entropy and mutual information are two measures of system complexity. We used entropy as a measure of the regularity of the number of agents in a social class; and mutual information as a measure of information shared by two social classes. Using our approaches, we compared two analogous agent-based (AB) models developed for regional-scale social-simulation system. The first AB model, called ABM-1, is a complex AB built with 10,000 agents on a desktop environment and used aggregate data; the second AB model, ABM-2, was built with 31 million agents on a highperformance computing framework located at Oak Ridge National Laboratory, and fine-resolution data from the LandScan Global Population Database. The initializations were slightly different, with ABM-1 using samples from a probability distribution and ABM-2 using polling data from Gallop for a deterministic initialization. The geographical and temporal domain was present-day Afghanistan, and the end result was the number of agents with one of three behavioral modes (proinsurgent, neutral, and pro-government) corresponding to the population mindshare. The theories embedded in each model were identical, and the test simulations focused on a test of three leadership theories - legitimacy, coercion, and representative, and two social mobilization theories - social influence and repression. The theories are tied together using the Cobb-Douglas utility function. Based on our results, the hypothesis that performance measures can be developed to compare and contrast AB models appears to be supported. Furthermore, we observed significant bias in the two models. Even so, further tests and investigations are required not only with a wider class of theories and AB models, but also with additional observed or simulated data and more comprehensive performance measures.

  18. Applications of Agent Based Approaches in Business (A Three Essay Dissertation)

    ERIC Educational Resources Information Center

    Prawesh, Shankar

    2013-01-01

    The goal of this dissertation is to investigate the enabling role that agent based simulation plays in business and policy. The aforementioned issue has been addressed in this dissertation through three distinct, but related essays. The first essay is a literature review of different research applications of agent based simulation in various…

  19. 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.

  20. 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.

  1. Irrigation Management, Evolving Canal Systems and Social Simulation in Hohokam Society, Central Arizona

    NASA Astrophysics Data System (ADS)

    Ertsen, Maurits; Murphy, John; Purdue, Louise

    2015-04-01

    As may societies that rely on irrigation, the Hohokam civilization in South West Arizona faced challenges arising from the variability and unpredictability of water supply and the physics underlying the flow of water through open channels. Such challenges can be overcome through cooperation and other forms of structured social interactions and institutions ranging from simple to complex. These interactions are influenced by and are influenced themselves by environmental conditions, including hydrology, soils and vegetation. At the same time, the environmental record provides clues to these interactions. To better understand these past interactions we combine geoarchaeological studies with flow simulations and Agent Based Modeling. Fieldwork conducted on Hohokam irrigation revealed new details about canal morphology, including shape, size, elevation, slope, and cleaning events. Micromorphological study of the sediments in these structures allow finer resolution in discerning the performance (velocity, discharge, etc.) of the canal channels and their evolution through time. We couple this with basic agent-based modeling to explore how these constraints might have required alternative strategies for cooperation. The combination of both approaches is key to discerning both broad differences between periods and fine variation within major chronological periods. We show that the coupling of social and physical models on very fine time scales can offer insight into the social arrangements and day-to-day life of people in the prehistoric past and inform our understanding of those societies' long-term changes.

  2. 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

  3. 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

  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. Trends in Social Science: The Impact of Computational and Simulative Models

    NASA Astrophysics Data System (ADS)

    Conte, Rosaria; Paolucci, Mario; Cecconi, Federico

    This paper discusses current progress in the computational social sciences. Specifically, it examines the following questions: Are the computational social sciences exhibiting positive or negative developments? What are the roles of agent-based models and simulation (ABM), network analysis, and other "computational" methods within this dynamic? (Conte, The necessity of intelligent agents in social simulation, Advances in Complex Systems, 3(01n04), 19-38, 2000; Conte 2010; Macy, Annual Review of Sociology, 143-166, 2002). Are there objective indicators of scientific growth that can be applied to different scientific areas, allowing for comparison among them? In this paper, some answers to these questions are presented and discussed. In particular, comparisons among different disciplines in the social and computational sciences are shown, taking into account their respective growth trends in the number of publication citations over the last few decades (culled from Google Scholar). After a short discussion of the methodology adopted, results of keyword-based queries are presented, unveiling some unexpected local impacts of simulation on the takeoff of traditionally poorly productive disciplines.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. NISAC Agent Based Laboratory for Economics

    SciTech Connect

    Downes, Paula; Davis, Chris; Eidson, Eric; Ehlen, Mark; Gieseler, Charles; Harris, Richard

    2006-10-11

    The software provides large-scale microeconomic simulation of complex economic and social systems (such as supply chain and market dynamics of businesses in the US economy) and their dependence on physical infrastructure systems. The system is based on Agent simulation, where each entity of inteest in the system to be modeled (for example, a Bank, individual firms, Consumer households, etc.) is specified in a data-driven sense to be individually repreented by an Agent. The Agents interact using rules of interaction appropriate to their roles, and through those interactions complex economic and social dynamics emerge. The software is implemented in three tiers, a Java-based visualization client, a C++ control mid-tier, and a C++ computational tier.

  11. Evolutionary game theory using agent-based methods.

    PubMed

    Adami, Christoph; Schossau, Jory; Hintze, Arend

    2016-12-01

    Evolutionary game theory is a successful mathematical framework geared towards understanding the selective pressures that affect the evolution of the strategies of agents engaged in interactions with potential conflicts. While a mathematical treatment of the costs and benefits of decisions can predict the optimal strategy in simple settings, more realistic settings such as finite populations, non-vanishing mutations rates, stochastic decisions, communication between agents, and spatial interactions, require agent-based methods where each agent is modeled as an individual, carries its own genes that determine its decisions, and where the evolutionary outcome can only be ascertained by evolving the population of agents forward in time. While highlighting standard mathematical results, we compare those to agent-based methods that can go beyond the limitations of equations and simulate the complexity of heterogeneous populations and an ever-changing set of interactors. We conclude that agent-based methods can predict evolutionary outcomes where purely mathematical treatments cannot tread (for example in the weak selection-strong mutation limit), but that mathematics is crucial to validate the computational simulations.

  12. Investigating biocomplexity through the agent-based paradigm

    PubMed Central

    Kaul, Himanshu

    2015-01-01

    Capturing the dynamism that pervades biological systems requires a computational approach that can accommodate both the continuous features of the system environment as well as the flexible and heterogeneous nature of component interactions. This presents a serious challenge for the more traditional mathematical approaches that assume component homogeneity to relate system observables using mathematical equations. While the homogeneity condition does not lead to loss of accuracy while simulating various continua, it fails to offer detailed solutions when applied to systems with dynamically interacting heterogeneous components. As the functionality and architecture of most biological systems is a product of multi-faceted individual interactions at the sub-system level, continuum models rarely offer much beyond qualitative similarity. Agent-based modelling is a class of algorithmic computational approaches that rely on interactions between Turing-complete finite-state machines—or agents—to simulate, from the bottom-up, macroscopic properties of a system. In recognizing the heterogeneity condition, they offer suitable ontologies to the system components being modelled, thereby succeeding where their continuum counterparts tend to struggle. Furthermore, being inherently hierarchical, they are quite amenable to coupling with other computational paradigms. The integration of any agent-based framework with continuum models is arguably the most elegant and precise way of representing biological systems. Although in its nascence, agent-based modelling has been utilized to model biological complexity across a broad range of biological scales (from cells to societies). In this article, we explore the reasons that make agent-based modelling the most precise approach to model biological systems that tend to be non-linear and complex. PMID:24227161

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. Agent based simulations in disease modeling Comment on "Towards a unified approach in the modeling of fibrosis: A review with research perspectives" by Martine Ben Amar and Carlo Bianca

    NASA Astrophysics Data System (ADS)

    Pappalardo, Francesco; Pennisi, Marzio

    2016-07-01

    Fibrosis represents a process where an excessive tissue formation in an organ follows the failure of a physiological reparative or reactive process. Mathematical and computational techniques may be used to improve the understanding of the mechanisms that lead to the disease and to test potential new treatments that may directly or indirectly have positive effects against fibrosis [1]. In this scenario, Ben Amar and Bianca [2] give us a broad picture of the existing mathematical and computational tools that have been used to model fibrotic processes at the molecular, cellular, and tissue levels. Among such techniques, agent based models (ABM) can give a valuable contribution in the understanding and better management of fibrotic diseases.

  18. 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.

  19. 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.

  20. Assurance in Agent-Based Systems

    SciTech Connect

    Gilliom, Laura R.; Goldsmith, Steven Y.

    1999-05-10

    Our vision of the future of information systems is one that includes engineered collectives of software agents which are situated in an environment over years and which increasingly improve the performance of the overall system of which they are a part. At a minimum, the movement of agent and multi-agent technology into National Security applications, including their use in information assurance, is apparent today. The use of deliberative, autonomous agents in high-consequence/high-security applications will require a commensurate level of protection and confidence in the predictability of system-level behavior. At Sandia National Laboratories, we have defined and are addressing a research agenda that integrates the surety (safety, security, and reliability) into agent-based systems at a deep level. Surety is addressed at multiple levels: The integrity of individual agents must be protected by addressing potential failure modes and vulnerabilities to malevolent threats. Providing for the surety of the collective requires attention to communications surety issues and mechanisms for identifying and working with trusted collaborators. At the highest level, using agent-based collectives within a large-scale distributed system requires the development of principled design methods to deliver the desired emergent performance or surety characteristics. This position paper will outline the research directions underway at Sandia, will discuss relevant work being performed elsewhere, and will report progress to date toward assurance in agent-based systems.

  1. Computerized Simulation in the Social Sciences: A Survey and Evaluation

    ERIC Educational Resources Information Center

    Garson, G. David

    2009-01-01

    After years at the periphery of the social sciences, simulation is now emerging as an important and widely used tool for understanding social phenomena. Through simulation, researchers can identify causal effects, specify critical parameter estimates, and clarify the state of the art with respect to what is understood about how processes evolve…

  2. 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.

  3. Debating the Future: A Social Security Political Leadership Simulation

    ERIC Educational Resources Information Center

    Rackaway, Chapman; Goertzen, Brent J.

    2008-01-01

    Students are well served by course simulations that employ active learning styles and student-driven interaction. For debate on political issues, particular public policies are quite effective in stimulating that discussion. We developed an in-class simulation of political debate on the issue of Social Security. We describe the simulation itself,…

  4. An agent-based microsimulation of critical infrastructure systems

    SciTech Connect

    BARTON,DIANNE C.; STAMBER,KEVIN L.

    2000-03-29

    US infrastructures provide essential services that support the economic prosperity and quality of life. Today, the latest threat to these infrastructures is the increasing complexity and interconnectedness of the system. On balance, added connectivity will improve economic efficiency; however, increased coupling could also result in situations where a disturbance in an isolated infrastructure unexpectedly cascades across diverse infrastructures. An understanding of the behavior of complex systems can be critical to understanding and predicting infrastructure responses to unexpected perturbation. Sandia National Laboratories has developed an agent-based model of critical US infrastructures using time-dependent Monte Carlo methods and a genetic algorithm learning classifier system to control decision making. The model is currently under development and contains agents that represent the several areas within the interconnected infrastructures, including electric power and fuel supply. Previous work shows that agent-based simulations models have the potential to improve the accuracy of complex system forecasting and to provide new insights into the factors that are the primary drivers of emergent behaviors in interdependent systems. Simulation results can be examined both computationally and analytically, offering new ways of theorizing about the impact of perturbations to an infrastructure network.

  5. Elements of a computational infrastructure for social simulation.

    PubMed

    Birkin, Mark; Procter, Rob; Allan, Rob; Bechhofer, Sean; Buchan, Iain; Goble, Carole; Hudson-Smith, Andy; Lambert, Paul; De Roure, David; Sinnott, Richard

    2010-08-28

    Applications of simulation modelling in social science domains are varied and increasingly widespread. The effective deployment of simulation models depends on access to diverse datasets, the use of analysis capabilities, the ability to visualize model outcomes and to capture, share and re-use simulations as evidence in research and policy-making. We describe three applications of e-social science that promote social simulation modelling, data management and visualization. An example is outlined in which the three components are brought together in a transport planning context. We discuss opportunities and benefits for the combination of these and other components into an e-infrastructure for social simulation and review recent progress towards the establishment of such an infrastructure.

  6. 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

  7. Immersive Simulation of Complex Social Environments

    DTIC Science & Technology

    2008-12-01

    evolution within a social group through interpersonal exchange (memetics). (Dawkins, 1987) Where genetic duplication tends to be precise (and mutation...is highly irregular), cultural evolution is prone to a number of elements that can quickly adapt itself to its surroundings. (Gu, 2008) Dennett...different cultural subgroups/factions) and inter-generational. (Dennett, 1995) Variability models explaining the evolution of social knowledge

  8. Puritan Day: A Social Science Simulation

    ERIC Educational Resources Information Center

    Schur, Joan Brodsky

    2007-01-01

    Most students assume that a thriving society runs smoothly because people abide by the laws. But there are various informal, as well as formal, means of social control such as gossip, ridicule, and shame that function even in complex societies to achieve social control, or conformity to group norms. Good teaching ideas have the potential to lead…

  9. 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.

  10. 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.

  11. Representing Dynamic Social Networks in Discrete Event Social Simulation

    DTIC Science & Technology

    2010-12-01

    applied settings in the areas of marketing and behavior modification programs (exercise adoption, smoking cessation) ( Icek Ajzen 2006). The model has an...society. The action choice component of the conceptual model is based on the theory of planned behavior (TPB) (I. Ajzen 1991). The TPB states that an...information networks into military simulations. In Pro- ceedings of the 40th Conference on Winter Simulation. pp. 133–144. Ajzen , I. 1991. The theory of

  12. An agent-based approach to financial stylized facts

    NASA Astrophysics Data System (ADS)

    Shimokawa, Tetsuya; Suzuki, Kyoko; Misawa, Tadanobu

    2007-06-01

    An important challenge of the financial theory in recent years is to construct more sophisticated models which have consistencies with as many financial stylized facts that cannot be explained by traditional models. Recently, psychological studies on decision making under uncertainty which originate in Kahneman and Tversky's research attract a lot of interest as key factors which figure out the financial stylized facts. These psychological results have been applied to the theory of investor's decision making and financial equilibrium modeling. This paper, following these behavioral financial studies, would like to propose an agent-based equilibrium model with prospect theoretical features of investors. Our goal is to point out a possibility that loss-averse feature of investors explains vast number of financial stylized facts and plays a crucial role in price formations of financial markets. Price process which is endogenously generated through our model has consistencies with, not only the equity premium puzzle and the volatility puzzle, but great kurtosis, asymmetry of return distribution, auto-correlation of return volatility, cross-correlation between return volatility and trading volume. Moreover, by using agent-based simulations, the paper also provides a rigorous explanation from the viewpoint of a lack of market liquidity to the size effect, which means that small-sized stocks enjoy excess returns compared to large-sized stocks.

  13. Affecting Socially Constructed Beliefs through Narrative Simulation.

    ERIC Educational Resources Information Center

    McCrary, Nancye

    This project explores the use of narrative to mediate the delivery of information on the effects of harmful discrimination in a simulated environment that is intended to arouse empathy and inspire reflection. It focuses on the potential of instructional narrative simulation to change biased beliefs about homosexuality. "This just is!"…

  14. 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.

  15. Simulations for Crisis Communication: The Use of Social Media

    ERIC Educational Resources Information Center

    Chung, Siyoung

    2016-01-01

    Simulations have been widely used in crisis and emergency communication for practitioners but have not reached classrooms in higher education. The purpose of this study was to investigate the effects that simulations using social media have on the learning of crisis communication among college students. To explore the effects, a real-time crisis…

  16. Exploring Complex Social Phenomena with Computer Simulations

    ERIC Educational Resources Information Center

    Berson, Ilene R.; Berson, Michael J.

    2007-01-01

    In social studies classes, there is a longstanding interest in how societies evolve and change over time. However, as stories of the past unfold, it is often difficult to identify a direct link between causes and effects, so students are forced to accept at face value the interpretations of economists, political scientists, historians,…

  17. 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.

  18. 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.

  19. 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.

  20. Prisoner's Dilemma as a Social Simulation Game.

    ERIC Educational Resources Information Center

    Glass, John F.

    A simulation game of strategy relating to alternate confession choices of two prisoners is described. The game, Prisoner's Dilemma, is designed to help participants learn about trust, cooperation, competition, intergroup dynamics, and their own life role and feelings. Three choices are offered at the beginning of the game to two prisoners, held…

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. Representing Trust in Cognitive Social Simulations

    DTIC Science & Technology

    2011-09-01

    must also want to spend time with you. The game now becomes a multiplayer integrated n-armed bandit game in which each of the agents will decide...tested using a public commodity game . Evaluation of the contributions and dividends within the public commodity game shows that many of the...network simulation and tested using a public commodity game . Evaluation of the contributions and dividends within the public commodity game shows

  6. Agent 2003 Conference on Challenges in Social Simulation

    SciTech Connect

    Margaret Clemmons, ed.

    2003-01-01

    Welcome to the Proceedings of the fourth in a series of agent simulation conferences cosponsored by Argonne National Laboratory and The University of Chicago. Agent 2003 is the second conference in which three Special Interest Groups from the North American Association for Computational Social and Organizational Science (NAACSOS) have been involved in planning the program--Computational Social Theory; Simulation Applications; and Methods, Toolkits and Techniques. The theme of Agent 2003, Challenges in Social Simulation, is especially relevant, as there seems to be no shortage of such challenges. Agent simulation has been applied with increasing frequency to social domains for several decades, and its promise is clear and increasingly visible. Like any nascent scientific methodology, however, it faces a number of problems or issues that must be addressed in order to progress. These challenges include: (1) Validating models relative to the social settings they are designed to represent; (2) Developing agents and interactions simple enough to understand but sufficiently complex to do justice to the social processes of interest; (3) Bridging the gap between empirically spare artificial societies and naturally occurring social phenomena; (4) Building multi-level models that span processes across domains; (5) Promoting a dialog among theoretical, qualitative, and empirical social scientists and area experts, on the one hand, and mathematical and computational modelers and engineers, on the other; (6) Using that dialog to facilitate substantive progress in the social sciences; and (7) Fulfilling the aspirations of users in business, government, and other application areas, while recognizing and addressing the preceding challenges. Although this list hardly exhausts the challenges the field faces, it does identify topics addressed throughout the presentations of Agent 2003. Agent 2003 is part of a much larger process in which new methods and techniques are applied to

  7. 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

  8. 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.

  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. 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

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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…

  17. USA Stratified Monopoly: A Simulation Game about Social Class Stratification

    ERIC Educational Resources Information Center

    Fisher, Edith M.

    2008-01-01

    Effectively teaching college students about social class stratification is a difficult challenge. Explanations for this difficulty tend to focus on the students who often react with resistance, paralysis, or rage. Sociologists have been using games and simulations as alternative methods for several decades to teach about these sensitive subjects.…

  18. Social Choice in a Computer-Assisted Simulation

    ERIC Educational Resources Information Center

    Thavikulwat, Precha

    2009-01-01

    Pursuing a line of inquiry suggested by Crookall, Martin, Saunders, and Coote, the author applied, within the framework of design science, an optimal-design approach to incorporate into a computer-assisted simulation two innovative social choice processes: the multiple period double auction and continuous voting. Expectations that the…

  19. 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.

  20. 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.

  1. Agent-Based Mapping of Credit Risk for Sustainable Microfinance

    PubMed Central

    Lee, Joung-Hun; Jusup, Marko; Podobnik, Boris; Iwasa, Yoh

    2015-01-01

    By drawing analogies with independent research areas, we propose an unorthodox framework for mapping microfinance credit risk---a major obstacle to the sustainability of lenders outreaching to the poor. Specifically, using the elements of network theory, we constructed an agent-based model that obeys the stylized rules of microfinance industry. We found that in a deteriorating economic environment confounded with adverse selection, a form of latent moral hazard may cause a regime shift from a high to a low loan payment probability. An after-the-fact recovery, when possible, required the economic environment to improve beyond that which led to the shift in the first place. These findings suggest a small set of measurable quantities for mapping microfinance credit risk and, consequently, for balancing the requirements to reasonably price loans and to operate on a fully self-financed basis. We illustrate how the proposed mapping works using a 10-year monthly data set from one of the best-known microfinance representatives, Grameen Bank in Bangladesh. Finally, we discuss an entirely new perspective for managing microfinance credit risk based on enticing spontaneous cooperation by building social capital. PMID:25945790

  2. Agent-based mapping of credit risk for sustainable microfinance.

    PubMed

    Lee, Joung-Hun; Jusup, Marko; Podobnik, Boris; Iwasa, Yoh

    2015-01-01

    By drawing analogies with independent research areas, we propose an unorthodox framework for mapping microfinance credit risk--a major obstacle to the sustainability of lenders outreaching to the poor. Specifically, using the elements of network theory, we constructed an agent-based model that obeys the stylized rules of microfinance industry. We found that in a deteriorating economic environment confounded with adverse selection, a form of latent moral hazard may cause a regime shift from a high to a low loan payment probability. An after-the-fact recovery, when possible, required the economic environment to improve beyond that which led to the shift in the first place. These findings suggest a small set of measurable quantities for mapping microfinance credit risk and, consequently, for balancing the requirements to reasonably price loans and to operate on a fully self-financed basis. We illustrate how the proposed mapping works using a 10-year monthly data set from one of the best-known microfinance representatives, Grameen Bank in Bangladesh. Finally, we discuss an entirely new perspective for managing microfinance credit risk based on enticing spontaneous cooperation by building social capital.

  3. Agent-based reasoning for distributed multi-INT analysis

    NASA Astrophysics Data System (ADS)

    Inchiosa, Mario E.; Parker, Miles T.; Perline, Richard

    2006-05-01

    Fully exploiting the intelligence community's exponentially growing data resources will require computational approaches differing radically from those currently available. Intelligence data is massive, distributed, and heterogeneous. Conventional approaches requiring highly structured and centralized data will not meet this challenge. We report on a new approach, Agent-Based Reasoning (ABR). In NIST evaluations, the use of ABR software tripled analysts' solution speed, doubled accuracy, and halved perceived difficulty. ABR makes use of populations of fine-grained, locally interacting agents that collectively reason about intelligence scenarios in a self-organizing, "bottom-up" process akin to those found in biological and other complex systems. Reproduction rules allow agents to make inferences from multi-INT data, while movement rules organize information and optimize reasoning. Complementary deterministic and stochastic agent behaviors enhance reasoning power and flexibility. Agent interaction via small-world networks - such as are found in nervous systems, social networks, and power distribution grids - dramatically increases the rate of discovering intelligence fragments that usefully connect to yield new inferences. Small-world networks also support the distributed processing necessary to address intelligence community data challenges. In addition, we have found that ABR pre-processing can boost the performance of commercial text clustering software. Finally, we have demonstrated interoperability with Knowledge Engineering systems and seen that reasoning across diverse data sources can be a rich source of inferences.

  4. 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.

  5. 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.

  6. 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.

  7. Investigating Ground Swarm Robotics Using Agent Based Simulation

    DTIC Science & Technology

    2006-12-01

    sensors and explosive detectors. These will be laid out further in Chapter II. Swarm robotics has attracted much attention because of the numerous key... attractive and repulsive force fields, which then control the dispersion and coverage of the swarm. Last but not least, Batalin and Sukhatme (2002) focused...of animals such as cockroaches , crickets, snakes and even lobsters (Ayers et al., 2002). Each of these species is highly efficient in mobility in

  8. Plan Validation Using DES and Agent-based Simulation

    DTIC Science & Technology

    2008-12-01

    a lock on A301 because in the model, a SAM site is only able to acquire a lock on one aircraft at a time, and since A302 and A301 are flying in...disengaged A302 and was assigned a new target A301 when A302 flies out of the gun’s firing range. The gun is behaving correctly. Target’s flight path Gun’s...A302 and starts to engage A301 . The gun is behaving correctly. Figure 39 Scenario for Target Switching When a Target is Killed A302 A301

  9. 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

  10. 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.

  11. Design of an Agent-Based Model to Examine Population-Environment Interactions in Nang Rong District, Thailand.

    PubMed

    Walsh, Stephen J; Malanson, George P; Entwisle, Barbara; Rindfuss, Ronald R; Mucha, Peter J; Heumann, Benjamin W; McDaniel, Philip M; Frizzelle, Brian G; Verdery, Ashton M; Williams, Nathalie; Xiaozheng, Yao; Ding, Deng

    2013-05-01

    The design of an Agent-Based Model (ABM) is described that integrates Social and Land Use Modules to examine population-environment interactions in a former agricultural frontier in Northeastern Thailand. The ABM is used to assess household income and wealth derived from agricultural production of lowland, rain-fed paddy rice and upland field crops in Nang Rong District as well as remittances returned to the household from family migrants who are engaged in off-farm employment in urban destinations. The ABM is supported by a longitudinal social survey of nearly 10,000 households, a deep satellite image time-series of land use change trajectories, multi-thematic social and ecological data organized within a GIS, and a suite of software modules that integrate data derived from an agricultural cropping system model (DSSAT - Decision Support for Agrotechnology Transfer) and a land suitability model (MAXENT - Maximum Entropy), in addition to multi-dimensional demographic survey data of individuals and households. The primary modules of the ABM are the Initialization Module, Migration Module, Assets Module, Land Suitability Module, Crop Yield Module, Fertilizer Module, and the Land Use Change Decision Module. The architecture of the ABM is described relative to module function and connectivity through uni-directional or bi-directional links. In general, the Social Modules simulate changes in human population and social networks, as well as changes in population migration and household assets, whereas the Land Use Modules simulate changes in land use types, land suitability, and crop yields. We emphasize the description of the Land Use Modules - the algorithms and interactions between the modules are described relative to the project goals of assessing household income and wealth relative to shifts in land use patterns, household demographics, population migration, social networks, and agricultural activities that collectively occur within a marginalized environment that

  12. Design of an Agent-Based Model to Examine Population-Environment Interactions in Nang Rong District, Thailand

    PubMed Central

    Walsh, Stephen J.; Malanson, George P.; Entwisle, Barbara; Rindfuss, Ronald R.; Mucha, Peter J.; Heumann, Benjamin W.; McDaniel, Philip M.; Frizzelle, Brian G.; Verdery, Ashton M.; Williams, Nathalie; Xiaozheng, Yao; Ding, Deng

    2013-01-01

    The design of an Agent-Based Model (ABM) is described that integrates Social and Land Use Modules to examine population-environment interactions in a former agricultural frontier in Northeastern Thailand. The ABM is used to assess household income and wealth derived from agricultural production of lowland, rain-fed paddy rice and upland field crops in Nang Rong District as well as remittances returned to the household from family migrants who are engaged in off-farm employment in urban destinations. The ABM is supported by a longitudinal social survey of nearly 10,000 households, a deep satellite image time-series of land use change trajectories, multi-thematic social and ecological data organized within a GIS, and a suite of software modules that integrate data derived from an agricultural cropping system model (DSSAT – Decision Support for Agrotechnology Transfer) and a land suitability model (MAXENT – Maximum Entropy), in addition to multi-dimensional demographic survey data of individuals and households. The primary modules of the ABM are the Initialization Module, Migration Module, Assets Module, Land Suitability Module, Crop Yield Module, Fertilizer Module, and the Land Use Change Decision Module. The architecture of the ABM is described relative to module function and connectivity through uni-directional or bi-directional links. In general, the Social Modules simulate changes in human population and social networks, as well as changes in population migration and household assets, whereas the Land Use Modules simulate changes in land use types, land suitability, and crop yields. We emphasize the description of the Land Use Modules – the algorithms and interactions between the modules are described relative to the project goals of assessing household income and wealth relative to shifts in land use patterns, household demographics, population migration, social networks, and agricultural activities that collectively occur within a marginalized environment

  13. Measure of Landscape Heterogeneity by Agent-Based Methodology

    NASA Astrophysics Data System (ADS)

    Wirth, E.; Szabó, Gy.; Czinkóczky, A.

    2016-06-01

    With the rapid increase of the world's population, the efficient food production is one of the key factors of the human survival. Since biodiversity and heterogeneity is the basis of the sustainable agriculture, the authors tried to measure the heterogeneity of a chosen landscape. The EU farming and subsidizing policies (EEA, 2014) support landscape heterogeneity and diversity, nevertheless exact measurements and calculations apart from statistical parameters (standard deviation, mean), do not really exist. In the present paper the authors' goal is to find an objective, dynamic method that measures landscape heterogeneity. It is achieved with the so called agent-based modelling, where randomly dispatched dynamic scouts record the observed land cover parameters and sum up the features of a new type of land. During the simulation the agents collect a Monte Carlo integral as a diversity landscape potential which can be considered as the unit of the `greening' measure. As a final product of the ABM method, a landscape potential map is obtained that can serve as a tool for objective decision making to support agricultural diversity.

  14. 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

  15. 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…

  16. Agent Based Intelligence in a Tetrahedral Rover

    NASA Technical Reports Server (NTRS)

    Phelps, Peter; Truszkowski, Walt

    2007-01-01

    A tetrahedron is a 4-node 6-strut pyramid structure which is being used by the NASA - Goddard Space Flight Center as the basic building block for a new approach to robotic motion. The struts are extendable; it is by the sequence of activities: strut-extension, changing the center of gravity and falling that the tetrahedron "moves". Currently, strut-extension is handled by human remote control. There is an effort underway to make the movement of the tetrahedron autonomous, driven by an attempt to achieve a goal. The approach being taken is to associate an intelligent agent with each node. Thus, the autonomous tetrahedron is realized as a constrained multi-agent system, where the constraints arise from the fact that between any two agents there is an extendible strut. The hypothesis of this work is that, by proper composition of such automated tetrahedra, robotic structures of various levels of complexity can be developed which will support more complex dynamic motions. This is the basis of the new approach to robotic motion which is under investigation. A Java-based simulator for the single tetrahedron, realized as a constrained multi-agent system, has been developed and evaluated. This paper reports on this project and presents a discussion of the structure and dynamics of the simulator.

  17. An Agent-Based Optimization Framework for Engineered Complex Adaptive Systems with Application to Demand Response in Electricity Markets

    NASA Astrophysics Data System (ADS)

    Haghnevis, Moeed

    The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.

  18. Smell Detection Agent Based Optimization Algorithm

    NASA Astrophysics Data System (ADS)

    Vinod Chandra, S. S.

    2016-09-01

    In this paper, a novel nature-inspired optimization algorithm has been employed and the trained behaviour of dogs in detecting smell trails is adapted into computational agents for problem solving. The algorithm involves creation of a surface with smell trails and subsequent iteration of the agents in resolving a path. This algorithm can be applied in different computational constraints that incorporate path-based problems. Implementation of the algorithm can be treated as a shortest path problem for a variety of datasets. The simulated agents have been used to evolve the shortest path between two nodes in a graph. This algorithm is useful to solve NP-hard problems that are related to path discovery. This algorithm is also useful to solve many practical optimization problems. The extensive derivation of the algorithm can be enabled to solve shortest path problems.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Agent Based Study of Surprise Attacks:. Roles of Surveillance, Prompt Reaction and Intelligence

    NASA Astrophysics Data System (ADS)

    Shanahan, Linda; Sen, Surajit

    Defending a confined territory from a surprise attack is seldom possible. We use molecular dynamics and statistical physics inspired agent-based simulations to explore the evolution and outcome of such attacks. The study suggests robust emergent behavior, which emphasizes the importance of accurate surveillance, automated and powerful attack response, building layout, and sheds light on the role of communication restrictions in defending such territories.

  6. 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.

  7. Deterministic Agent-Based Path Optimization by Mimicking the Spreading of Ripples.

    PubMed

    Hu, Xiao-Bing; Wang, Ming; Leeson, Mark S; Di Paolo, Ezequiel A; Liu, Hao

    2016-01-01

    Inspirations from nature have contributed fundamentally to the development of evolutionary computation. Learning from the natural ripple-spreading phenomenon, this article proposes a novel ripple-spreading algorithm (RSA) for the path optimization problem (POP). In nature, a ripple spreads at a constant speed in all directions, and the node closest to the source is the first to be reached. This very simple principle forms the foundation of the proposed RSA. In contrast to most deterministic top-down centralized path optimization methods, such as Dijkstra's algorithm, the RSA is a bottom-up decentralized agent-based simulation model. Moreover, it is distinguished from other agent-based algorithms, such as genetic algorithms and ant colony optimization, by being a deterministic method that can always guarantee the global optimal solution with very good scalability. Here, the RSA is specifically applied to four different POPs. The comparative simulation results illustrate the advantages of the RSA in terms of effectiveness and efficiency. Thanks to the agent-based and deterministic features, the RSA opens new opportunities to attack some problems, such as calculating the exact complete Pareto front in multiobjective optimization and determining the kth shortest project time in project management, which are very difficult, if not impossible, for existing methods to resolve. The ripple-spreading optimization principle and the new distinguishing features and capacities of the RSA enrich the theoretical foundations of evolutionary computation.

  8. Agent-based power sharing scheme for active hybrid power sources

    NASA Astrophysics Data System (ADS)

    Jiang, Zhenhua

    The active hybridization technique provides an effective approach to combining the best properties of a heterogeneous set of power sources to achieve higher energy density, power density and fuel efficiency. Active hybrid power sources can be used to power hybrid electric vehicles with selected combinations of internal combustion engines, fuel cells, batteries, and/or supercapacitors. They can be deployed in all-electric ships to build a distributed electric power system. They can also be used in a bulk power system to construct an autonomous distributed energy system. An important aspect in designing an active hybrid power source is to find a suitable control strategy that can manage the active power sharing and take advantage of the inherent scalability and robustness benefits of the hybrid system. This paper presents an agent-based power sharing scheme for active hybrid power sources. To demonstrate the effectiveness of the proposed agent-based power sharing scheme, simulation studies are performed for a hybrid power source that can be used in a solar car as the main propulsion power module. Simulation results clearly indicate that the agent-based control framework is effective to coordinate the various energy sources and manage the power/voltage profiles.

  9. 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.

  10. 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.

  11. Semantic Extension of Agent-Based Control: The Packing Cell Case Study

    NASA Astrophysics Data System (ADS)

    Vrba, Pavel; Radakovič, Miloslav; Obitko, Marek; Mařík, Vladimír

    The paper reports on the latest R&D activities in the field of agent-based manufacturing control systems. It is documented that this area becomes strongly influenced by the advancements of semantic technologies like the Web Ontology Language. The application of ontologies provides the agents with much more effective means for handling, exchanging and reasoning about the knowledge. The ontology dedicated for semantic description of orders, production processes and material handling tasks in discrete manufacturing domain has been developed. In addition, the framework for integration of this ontology in distributed, agent-based control solutions is given. The Manufacturing Agent Simulation Tool (MAST) is used as a base for pilot implementation of the ontology-powered multiagent control system; the packing cell environment is selected as a case study.

  12. 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.

  13. 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.

  14. The Hunt Opinion Model—An Agent Based Approach to Recurring Fashion Cycles

    PubMed Central

    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. PMID:27835679

  15. 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.

  16. 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

  17. 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

  18. Beat the Bourgeoisie: A Social Class Inequality and Mobility Simulation Game

    ERIC Educational Resources Information Center

    Norris, Dawn R.

    2013-01-01

    Simulation games can help overcome student resistance to thinking structurally about social class inequality, meritocracy, and mobility. Most inequality simulations focus solely on economic inequality and omit social and cultural capital, both of which contribute to social class reproduction. Using a pretest/posttest design, the current study…

  19. An Agent-Based Interface to Terrestrial Ecological Forecasting

    NASA Technical Reports Server (NTRS)

    Golden, Keith; Nemani, Ramakrishna; Pang, Wan-Lin; Votava, Petr; Etzioni, Oren

    2004-01-01

    This paper describes a flexible agent-based ecological forecasting system that combines multiple distributed data sources and models to provide near-real-time answers to questions about the state of the Earth system We build on novel techniques in automated constraint-based planning and natural language interfaces to automatically generate data products based on descriptions of the desired data products.

  20. The Uniframe Mobile Agent Based Resource Discovery Service

    DTIC Science & Technology

    2004-06-28

    ABSTRACT see report 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same as Report (SAR) 18 . NUMBER OF PAGES 251...Prescribed by ANSI Std Z39- 18 THE UNIFRAME MOBILE AGENT BASED RESOURCE DISCOVERY SERVICE A Technical Report Report Number TR-CIS... 18 2.1.2.3 The UniFrame System Level Generative Programming Framework (USGPF

  1. An Agent-based Framework for Web Query Answering.

    ERIC Educational Resources Information Center

    Wang, Huaiqing; Liao, Stephen; Liao, Lejian

    2000-01-01

    Discusses discrepancies between user queries on the Web and the answers provided by information sources; proposes an agent-based framework for Web mining tasks; introduces an object-oriented deductive data model and a flexible query language; and presents a cooperative mechanism for query answering. (Author/LRW)

  2. Agent-based services for B2B electronic commerce

    NASA Astrophysics Data System (ADS)

    Fong, Elizabeth; Ivezic, Nenad; Rhodes, Tom; Peng, Yun

    2000-12-01

    The potential of agent-based systems has not been realized yet, in part, because of the lack of understanding of how the agent technology supports industrial needs and emerging standards. The area of business-to-business electronic commerce (b2b e-commerce) is one of the most rapidly developing sectors of industry with huge impact on manufacturing practices. In this paper, we investigate the current state of agent technology and the feasibility of applying agent-based computing to b2b e-commerce in the circuit board manufacturing sector. We identify critical tasks and opportunities in the b2b e-commerce area where agent-based services can best be deployed. We describe an implemented agent-based prototype system to facilitate the bidding process for printed circuit board manufacturing and assembly. These activities are taking place within the Internet Commerce for Manufacturing (ICM) project, the NIST- sponsored project working with industry to create an environment where small manufacturers of mechanical and electronic components may participate competitively in virtual enterprises that manufacture printed circuit assemblies.

  3. 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

  4. A Two-Stage Multi-Agent Based Assessment Approach to Enhance Students' Learning Motivation through Negotiated Skills Assessment

    ERIC Educational Resources Information Center

    Chadli, Abdelhafid; Bendella, Fatima; Tranvouez, Erwan

    2015-01-01

    In this paper we present an Agent-based evaluation approach in a context of Multi-agent simulation learning systems. Our evaluation model is based on a two stage assessment approach: (1) a Distributed skill evaluation combining agents and fuzzy sets theory; and (2) a Negotiation based evaluation of students' performance during a training…

  5. Social-Cognitive Biases in Simulated Airline Luggage Screening

    NASA Technical Reports Server (NTRS)

    Brown, Jeremy R.; Madhavan, Poomima

    2011-01-01

    This study illustrated how social cognitive biases affect the decision making process of air1ine luggage screeners. Participants (n = 96) performed a computer simulated task to detect hidden weapons in 200 x-ray images of passenger luggage. Participants saw each image for two (high time pressure) or six seconds (low time pressure). Participants observed pictures of the "passenger" who owns the luggage . The "pre-anchor group" answered questions about the passenger before the luggage image appeared, the "post-snchor" group answered questions after the luggage appeared, and the "no-anchor group" answered no questions. Participants either stopped or did not stop the bag. and rated their confidence in their decision. Participants under high time pressure had lower hit rates and higher false alarms, Significant differences between the pre-, no-, and post-anchor groups were based on the gender and race of the passengers. Participants had higher false alarm rates in response to male than female passengers.

  6. 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.

  7. 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.

  8. 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.

  9. Simulating market dynamics: interactions between consumer psychology and social networks.

    PubMed

    Janssen, Marco A; Jager, Wander

    2003-01-01

    Markets can show different types of dynamics, from quiet markets dominated by one or a few products, to markets with continual penetration of new and reintroduced products. In a previous article we explored the dynamics of markets from a psychological perspective using a multi-agent simulation model. The main results indicated that the behavioral rules dominating the artificial consumer's decision making determine the resulting market dynamics, such as fashions, lock-in, and unstable renewal. Results also show the importance of psychological variables like social networks, preferences, and the need for identity to explain the dynamics of markets. In this article we extend this work in two directions. First, we will focus on a more systematic investigation of the effects of different network structures. The previous article was based on Watts and Strogatz's approach, which describes the small-world and clustering characteristics in networks. More recent research demonstrated that many large networks display a scale-free power-law distribution for node connectivity. In terms of market dynamics this may imply that a small proportion of consumers may have an exceptional influence on the consumptive behavior of others (hubs, or early adapters). We show that market dynamics is a self-organized property depending on the interaction between the agents' decision-making process (heuristics), the product characteristics (degree of satisfaction of unit of consumption, visibility), and the structure of interactions between agents (size of network and hubs in a social network).

  10. Social information and community dynamics: nontarget effects from simulating social cues for management.

    PubMed

    Fletcher, Robert J

    2008-10-01

    Artificially creating social stimuli may be an effective tool for facilitating settlement by rare and/or declining species into suitable habitat. However, the potential consequences for other community members have not been explored and should be considered when evaluating the overall utility of using such management strategies. I report on nontarget, community-wide effects that occurred when manipulating social cues of two competitors that are species of concern in the western United States, the dominant Least Flycatcher (Empidonax minimus) and the subordinate American Redstart (Setophaga ruticilla). The experiment consisted of surveying birds during a pretreatment year, which allows for the control of baseline communities, and a treatment year, in which treatments were applied just prior to settlement by migratory birds. Treatments included broadcasting songs of flycatchers and redstarts and were compared to controls. While the addition of redstart cues did not significantly influence community structure, the addition of flycatcher cues reduced species richness of migratory birds by approximately 30%. This pattern was driven by an absence of local colonizations of small-bodied migrants to sites with added flycatcher cues, rather than by local extinctions occurring from manipulations. The artificial flycatcher stimuli were more responsible for declines in species richness than were changes in actual flycatcher densities. I conclude by identifying some fundamental issues that managers and conservation practitioners should weigh when considering simulating social cues for species conservation prior to implementation.

  11. 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.

  12. Scalable, distributed data mining using an agent based architecture

    SciTech Connect

    Kargupta, H.; Hamzaoglu, I.; Stafford, B.

    1997-05-01

    Algorithm scalability and the distributed nature of both data and computation deserve serious attention in the context of data mining. This paper presents PADMA (PArallel Data Mining Agents), a parallel agent based system, that makes an effort to address these issues. PADMA contains modules for (1) parallel data accessing operations, (2) parallel hierarchical clustering, and (3) web-based data visualization. This paper describes the general architecture of PADMA and experimental results.

  13. On the Bridge to Learn: Analysing the Social Organization of Nautical Instruction in a Ship Simulator

    ERIC Educational Resources Information Center

    Hontvedt, Magnus; Arnseth, Hans Christian

    2013-01-01

    Research on simulator training has rarely focused on the way simulated contexts are constructed collaboratively. This study sheds light on how structuring role-play and fostering social interactions may prove fruitful for designing simulator training. The article reports on a qualitative study of nautical students training in a ship simulator. The…

  14. 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.

  15. 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.

  16. Simulating the effects of social networks on a population's hurricane evacuation participation

    NASA Astrophysics Data System (ADS)

    Widener, Michael J.; Horner, Mark W.; Metcalf, Sara S.

    2013-04-01

    Scientists have noted that recent shifts in the earth's climate have resulted in more extreme weather events, like stronger hurricanes. Such powerful storms disrupt societal function and result in a tremendous number of casualties, as demonstrated by recent hurricane experience in the US Planning for and facilitating evacuations of populations forecast to be impacted by hurricanes is perhaps the most effective strategy for reducing risk. A potentially important yet relatively unexplored facet of people's evacuation decision-making involves the interpersonal communication processes that affect whether at-risk residents decide to evacuate. While previous research has suggested that word-of-mouth effects are limited, data supporting these assertions were collected prior to the widespread adoption of digital social media technologies. This paper argues that the influence of social network effects on evacuation decisions should be revisited given the potential of new social media for impacting and augmenting information dispersion through real-time interpersonal communication. Using geographic data within an agent-based model of hurricane evacuation in Bay County, Florida, we examine how various types of social networks influence participation in evacuation. It is found that strategies for encouraging evacuation should consider the social networks influencing individuals during extreme events, as it can be used to increase the number of evacuating residents.

  17. 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.

  18. Breaking Frame in a Role-Play Simulation: A Language Socialization Perspective

    ERIC Educational Resources Information Center

    Schick, Laurie

    2008-01-01

    This article uses key concepts developed in frame analysis and language socialization theories to reconceptualize role-play simulation as socialization practice. The reconceptualization includes (a) an effort to explain an unexpected response to a role-play simulation on the topic of bullying and (b) a discussion regarding how this explanation…

  19. A Critical Appraisal of the Use of Standardized Client Simulations in Social Work Education

    ERIC Educational Resources Information Center

    Logie, Carmen; Bogo, Marion; Regehr, Cheryl; Regehr, Glenn

    2013-01-01

    Reliable and valid methods to evaluate student competence are needed in social work education, and practice examinations with standardized clients may hold promise for social work. The authors conducted a critical appraisal of standardized client simulations used in social work education to assess their effectiveness for teaching and for…

  20. The Game of Social Life: An Assessment of a Multidimensional Poverty Simulation

    ERIC Educational Resources Information Center

    Bramesfeld, Kosha D.; Good, Arla

    2015-01-01

    This article presents the development of a new simulation activity, the Game of Social Life. The activity introduces students to concepts of social stratification based on multiple dimensions of poverty, including inequalities related to housing, education, occupational status, social power, and health outcomes. The game was administered to…

  1. 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.

  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. 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

  4. 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.

  5. 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.

  6. Agent-Based Distributed Data Mining: A Survey

    NASA Astrophysics Data System (ADS)

    Moemeng, Chayapol; Gorodetsky, Vladimir; Zuo, Ziye; Yang, Yong; Zhang, Chengqi

    Distributed data mining is originated from the need of mining over decentralised data sources. Data mining techniques involving in such complex environment must encounter great dynamics due to changes in the system can affect the overall performance of the system. Agent computing whose aim is to deal with complex systems has revealed opportunities to improve distributed data mining systems in a number of ways. This paper surveys the integration of multi-agent system and distributed data mining, also known as agent-based distributed data mining, in terms of significance, system overview, existing systems, and research trends.

  7. 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

  8. Challenges in Computational Social Modeling and Simulation for National Security Decision Making

    DTIC Science & Technology

    2011-06-01

    Medicine Social work Military operations Intelligence National security Administration Social research Responsibility Accountability...such as finance and medicine [54]. It is not clear how to apply them to such a specific case as the development of social M&S tools to support NS...SIMULATION TOOLS: ETHICAL ASPECTS Unlike more established areas such as M&S for medicine , financial institutions, and management, social M&S for NS

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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

  20. Computational social dynamic modeling of group recruitment.

    SciTech Connect

    Berry, Nina M.; Lee, Marinna; Pickett, Marc; Turnley, Jessica Glicken; Smrcka, Julianne D.; Ko, Teresa H.; Moy, Timothy David; Wu, Benjamin C.

    2004-01-01

    The Seldon software toolkit combines concepts from agent-based modeling and social science to create a computationally social dynamic model for group recruitment. The underlying recruitment model is based on a unique three-level hybrid agent-based architecture that contains simple agents (level one), abstract agents (level two), and cognitive agents (level three). This uniqueness of this architecture begins with abstract agents that permit the model to include social concepts (gang) or institutional concepts (school) into a typical software simulation environment. The future addition of cognitive agents to the recruitment model will provide a unique entity that does not exist in any agent-based modeling toolkits to date. We use social networks to provide an integrated mesh within and between the different levels. This Java based toolkit is used to analyze different social concepts based on initialization input from the user. The input alters a set of parameters used to influence the values associated with the simple agents, abstract agents, and the interactions (simple agent-simple agent or simple agent-abstract agent) between these entities. The results of phase-1 Seldon toolkit provide insight into how certain social concepts apply to different scenario development for inner city gang recruitment.

  1. 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.

  2. 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.

  3. 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.

  4. Effectiveness of dynamic rescheduling in agent-based flexible manufacturing systems

    NASA Astrophysics Data System (ADS)

    Saad, Ashraf; Biswas, Gautam; Kawamura, Kazuhiko; Johnson, Eric M.

    1997-12-01

    This work has been developed within the framework of agent- based decentralized scheduling for flexible manufacturing systems. In this framework, all workcells comprising the manufacturing system, and the products to be generated, are modeled via intelligent software agents. These agents interact dynamically using a bidding production reservation (BPRS) scheme, based on the Contract Net Protocol, to devise the production schedule for each product unit. Simulation studies of a job shop have demonstrated the gains in performance achieved by this approach over heuristic dispatching rules commonly used in industry. Manufacturing environments are also prone to operational uncertainties such as variations in processing times and machine breakdowns. In order to cope with these uncertainties, the BPRS algorithm has been extended for dynamic rescheduling to also occur in a fully decentralized manner. The resulting multi-agent rescheduling scheme results in decentralized control of flexible manufacturing systems that are capable of responding dynamically to such operational uncertainties, thereby enhancing the robustness and fault tolerance of the proposed scheduling approach. This paper also presents the effects of the proposed agent-based decentralized scheduling approach on the performance of the underlying flexible manufacturing system under a variety of production and scheduling scenarios, including forward and backward scheduling. Future directions for this work include applying the proposed scheduling approach to other advanced manufacturing areas such as agile and holonic manufacturing.

  5. 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

  6. 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

  7. Engineering large-scale agent-based systems with consensus

    NASA Technical Reports Server (NTRS)

    Bokma, A.; Slade, A.; Kerridge, S.; Johnson, K.

    1994-01-01

    The paper presents the consensus method for the development of large-scale agent-based systems. Systems can be developed as networks of knowledge based agents (KBA) which engage in a collaborative problem solving effort. The method provides a comprehensive and integrated approach to the development of this type of system. This includes a systematic analysis of user requirements as well as a structured approach to generating a system design which exhibits the desired functionality. There is a direct correspondence between system requirements and design components. The benefits of this approach are that requirements are traceable into design components and code thus facilitating verification. The use of the consensus method with two major test applications showed it to be successful and also provided valuable insight into problems typically associated with the development of large systems.

  8. 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.

  9. 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

  10. Protection of autonomous microgrids using agent-based distributed communication

    SciTech Connect

    Cintuglu, Mehmet H.; Ma, Tan; Mohammed, Osama A.

    2016-04-06

    This study presents a real-time implementation of autonomous microgrid protection using agent-based distributed communication. Protection of an autonomous microgrid requires special considerations compared to large scale distribution net-works due to the presence of power converters and relatively low inertia. In this work, we introduce a practical overcurrent and a frequency selectivity method to overcome conventional limitations. The proposed overcurrent scheme defines a selectivity mechanism considering the remedial action scheme (RAS) of the microgrid after a fault instant based on feeder characteristics and the location of the intelligent electronic devices (IEDs). A synchrophasor-based online frequency selectivity approach is proposed to avoid pulse loading effects in low inertia microgrids. Experimental results are presented for verification of the pro-posed schemes using a laboratory based microgrid. The setup was composed of actual generation units and IEDs using IEC 61850 protocol. The experimental results were in excellent agreement with the proposed protection scheme.

  11. 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

  12. Simulating social interactions for the experimental investigation of joint attention.

    PubMed

    Caruana, Nathan; McArthur, Genevieve; Woolgar, Alexandra; Brock, Jon

    2017-03-01

    Social interactions are, by their nature, dynamic and reciprocal - your behaviour affects my behaviour, which affects your behaviour in return. However, until recently, the field of social cognitive neuroscience has been dominated by paradigms in which participants passively observe social stimuli from a detached "third person" perspective. Here we consider the unique conceptual and methodological challenges involved in adopting a "second person" approach whereby social cognitive mechanisms and their neural correlates are investigated within social interactions (Schilbach et al., 2013). The key question for researchers is how to distil a complex, intentional interaction between two individuals into a tightly controlled and replicable experimental paradigm. We explore these issues within the context of recent investigations of joint attention - the ability to coordinate a common focus of attention with another person. We review pioneering neurophysiology and eye-tracking studies that have begun to address these issues; offer recommendations for the optimal design and implementation of interactive tasks, and discuss the broader implications of interactive approaches for social cognitive neuroscience.

  13. 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.

  14. 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

  15. Simulating Real Life: Enhancing Social Work Education on Alcohol Screening and Brief Intervention

    ERIC Educational Resources Information Center

    Osborne, Victoria A.; Benner, Kalea; Sprague, Debra J.; Cleveland, Ivy N.

    2016-01-01

    Social work students typically use role play with student colleagues to practice clinical intervention skills. Practice with simulated clients (SCs) rather than classmates changes the dynamics of the role play and may improve learning. This is the first known study to employ the SC model in substance use assessment in social work education. Social…

  16. Student Perceptions of SocialSim for Simulation-Based Interprofessional Education in Healthcare

    ERIC Educational Resources Information Center

    Smith, Mary Kathryn

    2016-01-01

    This descriptive qualitative study investigates perceptions of students regarding the use of SocialSim, a tool designed to deliver simulation in a virtual environment using social media as a platform to facilitate inteprofessional education. There have been exponential changes in U.S. healthcare system in recent years, prompting the need for…

  17. 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

  18. Using Social Simulations to Assess and Train Potential Leaders to Make Effective Decisions in Turbulent Environments

    ERIC Educational Resources Information Center

    Hunsaker, L. Phillip

    2007-01-01

    Purpose: The purpose of this paper is to describe two social simulations created to assess leadership potential and train leaders to make effective decisions in turbulent environments. One is set in the novel environment of a lunar moon colony and the other is a military combat command. The research generated from these simulations for assessing…

  19. Simulated Family Therapy Interviews in Clinical Social Work Education

    ERIC Educational Resources Information Center

    Mooradian, John K.

    2007-01-01

    This article describes a learning method that employed theatre students as family clients in an advanced social work practice course. Students were provided with an opportunity to integrate and apply their learning of theory, clinical skills, and professional conduct in full-length family therapy sessions that occurred in the classroom and were…

  20. Complexity and Multifractal of Volatility Duration for Agent-Based Financial Dynamics and Real Markets

    NASA Astrophysics Data System (ADS)

    Yang, Ge; Wang, Jun

    2016-11-01

    A random agent-based financial model is developed and investigated by the finite-range multitype contact dynamic system, in an attempt to reproduce and study the dynamics of financial markets. And an analysis method of detecting duration and intensity relationship in volatility series is introduced, called the volatility duration analysis. Then the auto-correlation analysis suggests that there exists evident volatility clustering feature in absolute volatility durations for the simulation data and the real data. Besides, the Lempel-Ziv complexity analysis is applied to study the complexity of the returns, the corresponding absolute returns and the volatility duration returns, which can reflect the fluctuation behaviors, the volatility behaviors and the volatility duration behaviors. At last, the multifractal phenomena of volatility durations of returns are comparatively studied for Shanghai Composite Index and the proposed model by multifractal detrended fluctuation analysis.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Protection motivation theory and social distancing behaviour in response to a simulated infectious disease epidemic.

    PubMed

    Williams, Lynn; Rasmussen, Susan; Kleczkowski, Adam; Maharaj, Savi; Cairns, Nicole

    2015-01-01

    Epidemics of respiratory infectious disease remain one of the most serious health risks facing the population. Non-pharmaceutical interventions (e.g. hand-washing or wearing face masks) can have a significant impact on the course of an infectious disease epidemic. The current study investigated whether protection motivation theory (PMT) is a useful framework for understanding social distancing behaviour (i.e. the tendency to reduce social contacts) in response to a simulated infectious disease epidemic. There were 230 participants (109 males, 121 females, mean age 32.4 years) from the general population who completed self-report measures assessing the components of PMT. In addition, participants completed a computer game which simulated an infectious disease epidemic in order to provide a measure of social distancing behaviour. The regression analyses revealed that none of the PMT variables were significant predictors of social distancing behaviour during the simulation task. However, fear (β = .218, p < .001), response efficacy (β = .175, p < .01) and self-efficacy (β = .251, p < .001) were all significant predictors of intention to engage in social distancing behaviour. Overall, the PMT variables (and demographic factors) explain 21.2% of the variance in intention. The findings demonstrated that PMT was a useful framework for understanding intention to engage in social distancing behaviour, but not actual behaviour during the simulated epidemic. These findings may reflect an intention-behaviour gap in relation to social distancing behaviour.

  8. 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

  9. 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.

  10. Before and below 'theory of mind': embodied simulation and the neural correlates of social cognition.

    PubMed

    Gallese, Vittorio

    2007-04-29

    The automatic translation of folk psychology into newly formed brain modules specifically dedicated to mind-reading and other social cognitive abilities should be carefully scrutinized. Searching for the brain location of intentions, beliefs and desires-as such-might not be the best epistemic strategy to disclose what social cognition really is. The results of neurocognitive research suggest that in the brain of primates, mirror neurons, and more generally the premotor system, play a major role in several aspects of social cognition, from action and intention understanding to language processing. This evidence is presented and discussed within the theoretical frame of an embodied simulation account of social cognition. Embodied simulation and the mirror neuron system underpinning it provide the means to share communicative intentions, meaning and reference, thus granting the parity requirements of social communication.

  11. Protection of autonomous microgrids using agent-based distributed communication

    DOE PAGES

    Cintuglu, Mehmet H.; Ma, Tan; Mohammed, Osama A.

    2016-04-06

    This study presents a real-time implementation of autonomous microgrid protection using agent-based distributed communication. Protection of an autonomous microgrid requires special considerations compared to large scale distribution net-works due to the presence of power converters and relatively low inertia. In this work, we introduce a practical overcurrent and a frequency selectivity method to overcome conventional limitations. The proposed overcurrent scheme defines a selectivity mechanism considering the remedial action scheme (RAS) of the microgrid after a fault instant based on feeder characteristics and the location of the intelligent electronic devices (IEDs). A synchrophasor-based online frequency selectivity approach is proposed to avoidmore » pulse loading effects in low inertia microgrids. Experimental results are presented for verification of the pro-posed schemes using a laboratory based microgrid. The setup was composed of actual generation units and IEDs using IEC 61850 protocol. The experimental results were in excellent agreement with the proposed protection scheme.« less

  12. Correlation of etho-social and psycho-social data from "Mars-500" interplanetary simulation

    NASA Astrophysics Data System (ADS)

    Tafforin, Carole; Vinokhodova, Alla; Chekalina, Angelina; Gushin, Vadim

    2015-06-01

    Studies of social groups under isolation and confinement for the needs of space psychology were mostly limited by questionnaires completed with batteries of subjective tests, and they needed to be correlated with video recordings for objective analyses in space ethology. The aim of the present study is to identify crewmembers' behavioral profiles for better understanding group dynamics during a 520-day isolation and confinement of the international crew (n=6) participating to the "Mars-500" interplanetary simulation. We propose to correlate data from PSPA (Personal Self-Perception and Attitudes) computerized test, sociometric questionnaires and color choices test (Luscher test) used to measure anxiety levels, with data of video analysis during group discussion (GD) and breakfast time (BT). All the procedures were implemented monthly - GD, or twice a month - BT. Firstly, we used descriptive statistics for displaying quantitative subjects' behavioral profiles, supplied with a software based-solution: the Observer XT®. Secondly, we used Spearmen's nonparametric correlation analysis. The results show that for each subject, the level of non-verbal behavior ("visual interactions", "object interactions", "body interaction", "personal actions", "facial expressions", and "collateral acts") is higher than the level of verbal behavior ("interpersonal communication in Russian", and "interpersonal communication in English"). From the video analyses, dynamics profiles over months are different between the crewmembers. From the correlative analyses, we found highly negative correlations between anxiety and interpersonal communications; and between the sociometric parameter "popularity in leisure environment" and anxiety level. We also found highly significant positive correlations between the sociometric parameter "popularity in working environment" and interpersonal communications, and facial expressions; and between the sociometric parameter "popularity in leisure environment

  13. Effects of food ecology on social play: a laboratory simulation.

    PubMed

    Baldwin, J D; Baldwin, J I

    1976-01-01

    A laboratory group of 8 squirrel monkeys was exposed to two experimental conditions in which food was made moderately and extremely difficult to obtain, compared with the free access conditions of baseline. Both experiments produced sharp decreased in the frequency of social play within 4 to 6 days. The stronger manipulation produced the more dramatic effect, reducing play to 1% of the baseline level (P less than .001). Neither experiment produced a total absence of play as was observed in a previous field study in southwestern Panama (Baldwin and Baldwin 1973, 1974) which suggests that the field study sampled conditions of even more severe and/or prolonged food deprivation. No pathological or dysfunctional consequences were observed in any of the circumstances where play was reduced to zero or near zero. The question is raised whether certain theories of play have overstated the case for the necessity of play experience in producing normal socialization in primates. Alternative hypotheses are presented concerning the factors that determine the frequency of play and the consequences of play versus no-play for socialization. After both experiments, the frequency of play rose to a level 50% higher than the average baseline levels of play. This "rebound" reached a peak 5 to 6 days after the termination of each experiment; and during the subsequent days the frequency of play declined to more normal levels. A reinforcement theory is presented as a possible explanation of the rebound effect.

  14. A Social Diffusion Model with an Application on Election Simulation

    PubMed Central

    Wang, Fu-Min; Hung, San-Chuan; Kung, Perng-Hwa; Lin, Shou-De

    2014-01-01

    Issues about opinion diffusion have been studied for decades. It has so far no empirical approach to model the interflow and formation of crowd's opinion in elections due to two reasons. First, unlike the spread of information or flu, individuals have their intrinsic attitudes to election candidates in advance. Second, opinions are generally simply assumed as single values in most diffusion models. However, in this case, an opinion should represent preference toward multiple candidates. Previously done models thus may not intuitively interpret such scenario. This work is to design a diffusion model which is capable of managing the aforementioned scenario. To demonstrate the usefulness of our model, we simulate the diffusion on the network built based on a publicly available bibliography dataset. We compare the proposed model with other well-known models such as independent cascade. It turns out that our model consistently outperforms other models. We additionally investigate electoral issues with our model simulator. PMID:24995351

  15. A social diffusion model with an application on election simulation.

    PubMed

    Lou, Jing-Kai; Wang, Fu-Min; Tsai, Chin-Hua; Hung, San-Chuan; Kung, Perng-Hwa; Lin, Shou-De; Chen, Kuan-Ta; Lei, Chin-Laung

    2014-01-01

    Issues about opinion diffusion have been studied for decades. It has so far no empirical approach to model the interflow and formation of crowd's opinion in elections due to two reasons. First, unlike the spread of information or flu, individuals have their intrinsic attitudes to election candidates in advance. Second, opinions are generally simply assumed as single values in most diffusion models. However, in this case, an opinion should represent preference toward multiple candidates. Previously done models thus may not intuitively interpret such scenario. This work is to design a diffusion model which is capable of managing the aforementioned scenario. To demonstrate the usefulness of our model, we simulate the diffusion on the network built based on a publicly available bibliography dataset. We compare the proposed model with other well-known models such as independent cascade. It turns out that our model consistently outperforms other models. We additionally investigate electoral issues with our model simulator.

  16. Social Structure Simulation and Inference Using Artificial Intelligence Techniques

    DTIC Science & Technology

    2005-06-15

    effective and convenient avenues of attack against them. Another organizational analysis tool, DyNet [Carley, Dombroski, Tsve- tovat, Reminga, and...Kamneva, 2003] enables reasoning about dynamic net- worked organizations by adding a simulation component to MetaMatrix anal- ysis. The core tool is DyNet ...vulnerabilities, and their ability to reconstitute themselves. Using DyNet the analyst would be able to see how the networked organization was likely to evolve if

  17. 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

  18. A Novel Framework for Characterizing Exposure-Related Behaviors Using Agent-Based Models Embedded with Needs-Based Artificial Intelligence (CSSSA2016)

    EPA Science Inventory

    Descriptions of where and how individuals spend their time are important for characterizing exposures to chemicals in consumer products and in indoor environments. Herein we create an agent-based model (ABM) that is able to simulate longitudinal patterns in behaviors. By basing o...

  19. 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

  20. 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.

  1. 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

  2. A task-oriented modular and agent-based collaborative design mechanism for distributed product development

    NASA Astrophysics Data System (ADS)

    Liu, Jinfei; Chen, Ming; Wang, Lei; Wu, Qidi

    2014-05-01

    The rapid expansion of enterprises makes product collaborative design (PCD) a critical issue under the distributed heterogeneous environment, but as the collaborative task of large-scale network becomes more complicated, neither unified task decomposition and allocation methodology nor Agent-based network management platform can satisfy the increasing demands. In this paper, to meet requirements of PCD for distributed product development, a collaborative design mechanism based on the thought of modularity and the Agent technology is presented. First, the top-down 4-tier process model based on task-oriented modular and Agent is constructed for PCD after analyzing the mapping relationships between requirements and functions in the collaborative design. Second, on basis of sub-task decomposition for PCD based on a mixed method, the mathematic model of task-oriented modular based on multi-objective optimization is established to maximize the module cohesion degree and minimize the module coupling degree, while considering the module executable degree as a restriction. The mathematic model is optimized and simulated by the modified PSO, and the decomposed modules are obtained. Finally, the Agent structure model for collaborative design is put forward, and the optimism matching Agents are selected by using similarity algorithm to implement different task-modules by the integrated reasoning and decision-making mechanism with the behavioral model of collaborative design Agents. With the results of experimental studies for automobile collaborative design, the feasibility and efficiency of this methodology of task-oriented modular and Agent-based collaborative design in the distributed heterogeneous environment are verified. On this basis, an integrative automobile collaborative R&D platform is developed. This research provides an effective platform for automobile manufacturing enterprises to achieve PCD, and helps to promote product numeralization collaborative R&D and

  3. 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.

  4. 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.

  5. 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.

  6. Synthesis and Refinement of Detailed Subnetworks in a Social Contact Network for Epidemic Simulations

    NASA Astrophysics Data System (ADS)

    Xia, Huadong; Chen, Jiangzhuo; Marathe, Madhav; Mortveit, Henning S.

    In recent years, individual based epidemic simulations on synthetic social contact networks have been proved useful in supporting public health epidemiology. In use of such models, it is often desirable to understand how disease spreads through a small subset of the population; furthermore often data is available that allows us to develop more refined representations of social contact networks that span these sub-populations. Examples include: schools, office campuses, military bases, etc.

  7. 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…

  8. 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…

  9. 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

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Modeling Social Ties and Household Mobility

    PubMed Central

    Metcalf, Sara S.

    2013-01-01

    Underlying the aggregate phenomena of persistent problems such as urban sprawl and spatial socio-economic disparity is the individual choice of where to live. This study develops an agent-based model to simulate social and economic influences on neighborhood choice. With Danville, Illinois as an empirical context, a pattern-oriented approach is employed to examine the role of social ties in shaping intra-urban household mobility. In the model, household agents decide whether and where to relocate within the community based upon factors such as neighborhood attractiveness, affordability, and the density of a household's social network in the prospective block group. Social network and neighborhood choices are encoded with logit utility functions. The relative influence of factors affecting the formation of social ties in the simulated social network, such as geographic proximity, similarity of income, race, and presence of children, are adjusted using parameter variation to create alternative model settings. Simulated migration patterns resulting from different network and neighborhood choice coefficients are compared with observed migration patterns over a two-year period. Based upon 1000 simulation experiments, a regression of homeowner migration error (the difference between simulated and observed migration) relative to the parameter settings revealed components of social network choice such as income, race, and probability of local ties to be significant in matching observed migration patterns. A non-linear effect of simulated social networks on household mobility and thus migration error was exhibited in this study. PMID:25035520

  18. Modeling Social Ties and Household Mobility.

    PubMed

    Metcalf, Sara S

    2014-01-01

    Underlying the aggregate phenomena of persistent problems such as urban sprawl and spatial socio-economic disparity is the individual choice of where to live. This study develops an agent-based model to simulate social and economic influences on neighborhood choice. With Danville, Illinois as an empirical context, a pattern-oriented approach is employed to examine the role of social ties in shaping intra-urban household mobility. In the model, household agents decide whether and where to relocate within the community based upon factors such as neighborhood attractiveness, affordability, and the density of a household's social network in the prospective block group. Social network and neighborhood choices are encoded with logit utility functions. The relative influence of factors affecting the formation of social ties in the simulated social network, such as geographic proximity, similarity of income, race, and presence of children, are adjusted using parameter variation to create alternative model settings. Simulated migration patterns resulting from different network and neighborhood choice coefficients are compared with observed migration patterns over a two-year period. Based upon 1000 simulation experiments, a regression of homeowner migration error (the difference between simulated and observed migration) relative to the parameter settings revealed components of social network choice such as income, race, and probability of local ties to be significant in matching observed migration patterns. A non-linear effect of simulated social networks on household mobility and thus migration error was exhibited in this study.

  19. 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.

  20. Agent-Based Model Forecasts Aging of the Population of People Who Inject Drugs in Metropolitan Chicago and Changing Prevalence of Hepatitis C Infections.

    PubMed

    Gutfraind, Alexander; Boodram, Basmattee; Prachand, Nikhil; Hailegiorgis, Atesmachew; Dahari, Harel; Major, Marian E

    2015-01-01

    People who inject drugs (PWID) are at high risk for blood-borne pathogens transmitted during the sharing of contaminated injection equipment, particularly hepatitis C virus (HCV). HCV prevalence is influenced by a complex interplay of drug-use behaviors, social networks, and geography, as well as the availability of interventions, such as needle exchange programs. To adequately address this complexity in HCV epidemic forecasting, we have developed a computational model, the Agent-based Pathogen Kinetics model (APK). APK simulates the PWID population in metropolitan Chicago, including the social interactions that result in HCV infection. We used multiple empirical data sources on Chicago PWID to build a spatial distribution of an in silico PWID population and modeled networks among the PWID by considering the geography of the city and its suburbs. APK was validated against 2012 empirical data (the latest available) and shown to agree with network and epidemiological surveys to within 1%. For the period 2010-2020, APK forecasts a decline in HCV prevalence of 0.8% per year from 44(± 2)% to 36(± 5)%, although some sub-populations would continue to have relatively high prevalence, including Non-Hispanic Blacks, 48(± 5)%. The rate of decline will be lowest in Non-Hispanic Whites and we find, in a reversal of historical trends, that incidence among non-Hispanic Whites would exceed incidence among Non-Hispanic Blacks (0.66 per 100 per years vs 0.17 per 100 person years). APK also forecasts an increase in PWID mean age from 35(± 1) to 40(± 2) with a corresponding increase from 59(± 2)% to 80(± 6)% in the proportion of the population >30 years old. Our studies highlight the importance of analyzing subpopulations in disease predictions, the utility of computer simulation for analyzing demographic and health trends among PWID and serve as a tool for guiding intervention and prevention strategies in Chicago, and other major cities.

  1. Using Simulation Technology To Promote Social Competence of Handicapped Students. Brief Final Report.

    ERIC Educational Resources Information Center

    Denver Univ., CO. Denver Research Inst.

    This federally-funded project developed computer-based simulations in the area of job-related social skills for youth, ages 16-21, who are handicapped and are in transition between school and work (i.e., high school juniors and seniors). This population included students with learning disabilities, mild retardation, and emotional disturbances. The…

  2. 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

  3. 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

  4. 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..

  5. An Agent-Based Architecture for Generating Interactive Stories

    DTIC Science & Technology

    2002-09-01

    Mateas, 1997], [Blumberg, 1996], [Hayes-Roth et al., 1996] and [Rickel et al., 2001]. However, the body of work on developing systems where the...without detailed planning. The underlying agent architecture centers around a mind- body design. The mind is the implementation of a social-psychological...external inputs and stimuli, controls the agents decisions and provides input to the body . The body is the expression of the actions selected by

  6. 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.

  7. Modified social force model based on information transmission toward crowd evacuation simulation

    NASA Astrophysics Data System (ADS)

    Han, Yanbin; Liu, Hong

    2017-03-01

    In this paper, the information transmission mechanism is introduced into the social force model to simulate pedestrian behavior in an emergency, especially when most pedestrians are unfamiliar with the evacuation environment. This modified model includes a collision avoidance strategy and an information transmission model that considers information loss. The former is used to avoid collision among pedestrians in a simulation, whereas the latter mainly describes how pedestrians obtain and choose directions appropriate to them. Simulation results show that pedestrians can obtain the correct moving direction through information transmission mechanism and that the modified model can simulate actual pedestrian behavior during an emergency evacuation. Moreover, we have drawn four conclusions to improve evacuation based on the simulation results; and these conclusions greatly contribute in optimizing a number of efficient emergency evacuation schemes for large public places.

  8. 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.

  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. 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.

  11. 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.

  12. 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.

  13. Agent-based Modeling Methodology for Analyzing Weapons Systems

    DTIC Science & Technology

    2015-03-26

    Air Force Research Laboratory’s Sweep Mission Scenario for the Spartacus Study (Geaslen & Panson, 2014). 59 Figure 28: AFSIM Simulation...Reactive Technology for an Advanced Combat Utility System ( SPARTACUS ) Air Combat Development Scenario. Wright Patterson Air Force Base OH: Air Force

  14. 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

  15. Can Multimedia Make Kids Care about Social Studies? The GlobalEd Problem-Based Learning Simulation

    ERIC Educational Resources Information Center

    Ioannou, Andri; Brown, Scott W.; Hannafin, Robert D.; Boyer, Mark A.

    2009-01-01

    This study investigated whether using multimedia-based instructional material in a problem-based social studies simulation enhances student learning about world issues, increases interest in social studies, and generates positive attitudes toward the instruction. The GlobalEd Project, a Web-based international negotiation simulation embedded in…

  16. 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

  17. 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.

  18. Are you real? Visual simulation of social housing by mirror image stimulation in single housed mice.

    PubMed

    Fuss, Johannes; Richter, S Helene; Steinle, Jörg; Deubert, Gerald; Hellweg, Rainer; Gass, Peter

    2013-04-15

    Individual housing of social species is a common phenomenon in laboratory animal facilities. Single housing, however, is known to inflict social deprivation with a number of detrimental consequences. Aiming to improve housing conditions of single housed rodents, we investigated the simulation of social housing by mirrors in a series of behavioural experiments and biochemical parameters in mice. We found that chronic mirror-image stimulation increased exploratory behaviours in the holeboard and novel cage tests, but did not alter anxiety, locomotor, or depression-like behaviours. Moreover, no influence on visual recognition memory was observed. Hippocampal brain-derived neurotrophic factor (BDNF) levels, a biomarker for enrichment effects, were unaltered. In line, mirror-image stimulation did not alter home cage behaviour in mice housed with and without mirrors when left undisturbed. Thus, though we found subtle behavioural effects after long-term mirror exposure, we conclude that the simulation of social housing by mirrors is not sufficient to gain the presumably beneficial outcomes induced by social housing.

  19. Customer social network affects marketing strategy: A simulation analysis based on competitive diffusion model

    NASA Astrophysics Data System (ADS)

    Hou, Rui; Wu, Jiawen; Du, Helen S.

    2017-03-01

    To explain the competition phenomenon and results between QQ and MSN (China) in the Chinese instant messaging software market, this paper developed a new population competition model based on customer social network. The simulation results show that the firm whose product with greater network externality effect will gain more market share than its rival when the same marketing strategy is used. The firm with the advantage of time, derived from the initial scale effect will become more competitive than its rival when facing a group of common penguin customers within a social network, verifying the winner-take-all phenomenon in this case.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. Development and evaluation of liquid embolic agents based on liquid crystalline material of glyceryl monooleate.

    PubMed

    Du, Ling-Ran; Lu, Xiao-Jing; Guan, Hai-Tao; Yang, Yong-Jie; Gu, Meng-Jie; Zheng, Zhuo-Zhao; Lv, Tian-Shi; Yan, Zi-Guang; Song, Li; Zou, Ying-Hua; Fu, Nai-Qi; Qi, Xian-Rong; Fan, Tian-Yuan

    2014-08-25

    New type of liquid embolic agents based on a liquid crystalline material of glyceryl monooleate (GMO) was developed and evaluated in this study. Ternary phase diagram of GMO, water and ethanol was constructed and three isotropic liquids (ILs, GMO:ethanol:water=49:21:30, 60:20:20 and 72:18:10 (w/w/w)) were selected as potential liquid embolic agents, which could spontaneously form viscous gel cast when contacting with water or physiological fluid. The ILs exhibited excellent microcatheter deliverability due to low viscosity, and were proved to successfully block the saline flow when performed in a device to simulate embolization in vitro. The ILs also showed good cytocompatibility on L929 mouse fibroblast cell line. The embolization of ILs to rabbit kidneys was performed successfully under monitoring of digital subtraction angiography (DSA), and embolic degree was affected by the initial formulation composition and used volume. At 5th week after embolization, DSA and computed tomography (CT) confirmed the renal arteries embolized with IL did not recanalize in follow-up period, and an obvious atrophy of the embolized kidney was observed. Therefore, the GMO-based liquid embolic agents showed feasible and effective to embolize, and potential use in clinical interventional embolization therapy.

  5. 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.

  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. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Distributed Multi-Agent-Based Protection Scheme for Transient Stability Enhancement in Power Systems

    NASA Astrophysics Data System (ADS)

    Rahman, M. S.; Mahmud, M. A.; Pota, H. R.; Hossain, M. J.; Orchi, T. F.

    2015-04-01

    This paper presents a new distributed agent-based scheme to enhance the transient stability of power systems by maintaining phase angle cohesiveness of interconnected generators through proper relay coordination with critical clearing time (CCT) information. In this distributed multi-agent infrastructure, intelligent agents represent various physical device models to provide dynamic information and energy flow among different physical processes of power systems. The agents can communicate with each other in a distributed manner with a final aim to control circuit breakers (CBs) with CCT information as this is the key issue for maintaining and enhancing the transient stability of power systems. The performance of the proposed scheme is evaluated on a standard IEEE 39-bus New England benchmark system under different large disturbances such as three-phase short-circuit faults and changes in loads within the systems. From the simulation results, it is found that the proposed scheme significantly enhances the transient stability of power systems as compared to a conventional scheme of static CB operation.

  13. 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.

  14. 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

  15. Absorptivity of molded soil-improving agents based on brown coals and zeolites

    SciTech Connect

    Aleksandrov, I.V.; Kossov, I.I.

    1993-12-31

    The objective of this work was to create a new technique for producing molded soil-improving agents based on brown coal from the Adunchulun deposit, and to determine the soil-improving properties of the obtained compositions.

  16. Virtual Reality for Artificial Intelligence: human-centered simulation for social science.

    PubMed

    Cipresso, Pietro; Riva, Giuseppe

    2015-01-01

    There is a long last tradition in Artificial Intelligence as use of Robots endowing human peculiarities, from a cognitive and emotional point of view, and not only in shape. Today Artificial Intelligence is more oriented to several form of collective intelligence, also building robot simulators (hardware or software) to deeply understand collective behaviors in human beings and society as a whole. Modeling has also been crucial in the social sciences, to understand how complex systems can arise from simple rules. However, while engineers' simulations can be performed in the physical world using robots, for social scientist this is impossible. For decades, researchers tried to improve simulations by endowing artificial agents with simple and complex rules that emulated human behavior also by using artificial intelligence (AI). To include human beings and their real intelligence within artificial societies is now the big challenge. We present an hybrid (human-artificial) platform where experiments can be performed by simulated artificial worlds in the following manner: 1) agents' behaviors are regulated by the behaviors shown in Virtual Reality involving real human beings exposed to specific situations to simulate, and 2) technology transfers these rules into the artificial world. These form a closed-loop of real behaviors inserted into artificial agents, which can be used to study real society.

  17. Modeling social norms and social influence in obesity

    PubMed Central

    Shoham, David A.; Hammond, Ross; Rahmandad, Hazhir; Wang, Youfa; Hovmand, Peter

    2015-01-01

    The worldwide increase in obesity has led to changes in what is considered “normal” or desirable weight, especially among populations at higher risk. We show that social norms are key to understanding the obesity epidemic, and that social influence mechanisms provide a necessary linkage between individual obesity-related behaviors and population-level characteristics. Because influence mechanisms cannot be directly observed, we show how three complex systems tools may be used to gain insights into observed epidemiologic patterns: social network analysis, agent-based modeling, and systems dynamics modeling. However, simulation and mathematical modeling approaches raise questions regarding acceptance of findings, especially among policy makers. Nevertheless, we point to modeling successes in obesity and other fields, including the NIH-funded National Collaborative on Childhood Obesity Research (NCCOR) Envison project. PMID:26576335

  18. 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

  19. Context-Driven Decision Making in Network-Centric Operations: Agent-Based Intelligent Support

    DTIC Science & Technology

    2006-01-01

    SPIIRAS CKM Workshop (MIT, Cambridge, MA; January 24, 2006 Context-Driven Decision Making in Network-Centric Operations: Agent- Based Intelligent...Operations: Agent- Based Intelligent Support 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK...Enterprise and Multi-Agent Systems (Engineering and Physical Sciences Research Council, UK, 2003-2005) Ontology- Based New Order Code Generation for

  20. 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.

  1. 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.

  2. Towards oscillations-based simulation of social systems: a neurodynamic approach

    NASA Astrophysics Data System (ADS)

    Plikynas, Darius; Basinskas, Gytis; Laukaitis, Algirdas

    2015-04-01

    This multidisciplinary work presents synopsis of theories in the search for common field-like fundamental principles of self-organisation and communication existing on quantum, cellular, and even social levels. Based on these fundamental principles, we formulate conceptually novel social neuroscience paradigm (OSIMAS), which envisages social systems emerging from the coherent neurodynamical processes taking place in the individual mind-fields. In this way, societies are understood as global processes emerging from the superposition of the conscious and subconscious mind-fields of individual members of society. For the experimental validation of the biologically inspired OSIMAS paradigm, we have designed a framework of EEG-based experiments. Initial baseline individual tests of spectral cross-correlations of EEG-recorded brainwave patterns for some mental states have been provided in this paper. Preliminary experimental results do not refute the main OSIMAS postulates. This paper also provides some insights for the construction of OSIMAS-based simulation models.

  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. 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. Personality, social support and affective states during simulated microgravity in healthy women

    NASA Astrophysics Data System (ADS)

    Nicolas, Michel

    2009-12-01

    This study investigated the time-course of stress and recovery states and their relations to social support and personality traits in healthy women during a long-term head-down tilt bed rest. Personality, social support and affective states were assessed in 16 women exposed to simulated microgravity for a 60-day duration involving three stages: a 20-day baseline control period (BDC), a 60-day head-down tilt bed rest (HDT) and a 20-day post-HDT ambulatory recovery period (R+). Participants were divided into two groups: an exercise (Exe, n = 8) and a control group (Ctl, n = 8). All the participants experienced significantly more stress during the HDT period. But exercise did not improve the impaired effects of simulated microgravity. The Exe group perceived more stress and less recovery than the Ctl group during the HDT period. Among the five major personality factors, only Neuroticism was related to both social and affective variables. Neuroticism was positively associated with stress and negatively associated with recovery and social support (S-SSQ). Practical implications in psychological countermeasures for better dealing with the key human factor in spaceflights are discussed.

  6. The collective-risk social dilemma and the prevention of simulated dangerous climate change.

    PubMed

    Milinski, Manfred; Sommerfeld, Ralf D; Krambeck, Hans-Jürgen; Reed, Floyd A; Marotzke, Jochem

    2008-02-19

    Will a group of people reach a collective target through individual contributions when everyone suffers individually if the target is missed? This "collective-risk social dilemma" exists in various social scenarios, the globally most challenging one being the prevention of dangerous climate change. Reaching the collective target requires individual sacrifice, with benefits to all but no guarantee that others will also contribute. It even seems tempting to contribute less and save money to induce others to contribute more, hence the dilemma and the risk of failure. Here, we introduce the collective-risk social dilemma and simulate it in a controlled experiment: Will a group of people reach a fixed target sum through successive monetary contributions, when they know they will lose all their remaining money with a certain probability if they fail to reach the target sum? We find that, under high risk of simulated dangerous climate change, half of the groups succeed in reaching the target sum, whereas the others only marginally fail. When the risk of loss is only as high as the necessary average investment or even lower, the groups generally fail to reach the target sum. We conclude that one possible strategy to relieve the collective-risk dilemma in high-risk situations is to convince people that failure to invest enough is very likely to cause grave financial loss to the individual. Our analysis describes the social window humankind has to prevent dangerous climate change.

  7. Tracking and simulating dynamics of implicit stereotypes: A situated social cognition perspective.

    PubMed

    Smeding, Annique; Quinton, Jean-Charles; Lauer, Kelly; Barca, Laura; Pezzulo, Giovanni

    2016-12-01

    Adopting a situated social cognition perspective, we relied on different methodologies-1 computational and 3 empirical studies-to investigate social group-related specificities pertaining to implicit gender-domain stereotypes, as measured by a mouse-tracking adapted Implicit Association Test (IAT) and IAT(-like) tasks. We tested whether the emergence of implicit stereotypes was partially determined by associations congruent with the self, by visuospatial features of the task and subsequent competition at both sensorimotor and abstract levels. We tracked human and simulated artificial participants' hand movements among gender stereotypical (e.g., male engineers) and counterstereotypical (e.g., female engineers) social groups. In the computational study, data were simulated by a novel generative connectionist model integrating strengths from recent developments in embodied models of decision-making. Results support the self-congruency hypothesis and suggest the presence of competition at both levels. Discussion focuses on the generalizability of the self-congruency hypothesis and on the relevance of a situated perspective for implicit social cognition. (PsycINFO Database Record

  8. 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.

  9. Adaptivity in Agent-Based Routing for Data Networks

    NASA Technical Reports Server (NTRS)

    Wolpert, David H.; Kirshner, Sergey; Merz, Chris J.; Turner, Kagan

    2000-01-01

    Adaptivity, both of the individual agents and of the interaction structure among the agents, seems indispensable for scaling up multi-agent systems (MAS s) in noisy environments. One important consideration in designing adaptive agents is choosing their action spaces to be as amenable as possible to machine learning techniques, especially to reinforcement learning (RL) techniques. One important way to have the interaction structure connecting agents itself be adaptive is to have the intentions and/or actions of the agents be in the input spaces of the other agents, much as in Stackelberg games. We consider both kinds of adaptivity in the design of a MAS to control network packet routing. We demonstrate on the OPNET event-driven network simulator the perhaps surprising fact that simply changing the action space of the agents to be better suited to RL can result in very large improvements in their potential performance: at their best settings, our learning-amenable router agents achieve throughputs up to three and one half times better than that of the standard Bellman-Ford routing algorithm, even when the Bellman-Ford protocol traffic is maintained. We then demonstrate that much of that potential improvement can be realized by having the agents learn their settings when the agent interaction structure is itself adaptive.

  10. 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.

  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. 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

  13. 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.

  14. 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

  15. 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).

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. Social systems in terms of coherent individual neurodynamics: conceptual premises, experimental and simulation scope

    NASA Astrophysics Data System (ADS)

    Plikynas, Darius; Basinskas, Gytis; Kumar, Pravin; Masteika, Saulius; Kezys, Darius; Laukaitis, Algirdas

    2014-07-01

    After reviewing numerous theories and experiments, our research adopted the field-theoretical deductive approach to shed new light on complex social systems as coherent neurodynamic processes taking place in individual minds. In this interdisciplinary study, we have outlined some general fundamental design principles of the field-theoretical view of the oscillating agent as well as of coherent social systems. From the systems point of view, ordered social systems by their own intrinsic nature are interpreted as coherent activations via the mind-field medium of social agents. Consequently, this study not only provides the major conceptual assumptions of the proposed (Oscillation-Based Multi-Agent System [OSIMAS]) paradigm but also presents an electroencephalography-based inductive experimental validation framework and some empirical results to validate major OSIMAS assumptions. Based on the conceptual and experimental findings, we constructed modelling framework and presented oscillations-based micro (coupled oscillator energy exchange model) and macro (MEPSM1) simulation models. We also systemized some other studies and applications, which are most relevant to the work presented here.

  1. Social learning by orangutans (Pongo abelii and Pongo pygmaeus) in a simulated food-processing task.

    PubMed

    Stoinski, Tara S; Whiten, Andrew

    2003-09-01

    Increasing evidence for behavioral differences between populations of primates has created a resurgence of interest in examining mechanisms of information transfer between individuals. The authors examined the social transmission of information in 15 captive orangutans (Pongo abelii and Pongo pygmaeus) using a simulated food-processing task. Experimental subjects were shown 1 of 2 methods for removing a suite of defenses on an "artificial fruit." Control subjects were given no prior exposure before interacting with the fruit. Observing a model provided a functional advantage in the task, as significantly more experimental than control subjects opened the fruit. Within the experimental groups, the authors found a trend toward differences in the actual behaviors used to remove 1 of the defenses. Results support observations from the wild implying horizontal transfer of information in orangutans and show that a number of social learning processes are likely to be involved in the transfer of knowledge in this species.

  2. Virtually simulated social pressure influences early visual processing more in low compared to high autonomous participants.

    PubMed

    Trautmann-Lengsfeld, Sina Alexa; Herrmann, Christoph Siegfried

    2014-02-01

    In a previous study, we showed that virtually simulated social group pressure could influence early stages of perception after only 100  ms. In the present EEG study, we investigated the influence of social pressure on visual perception in participants with high (HA) and low (LA) levels of autonomy. Ten HA and ten LA individuals were asked to accomplish a visual discrimination task in an adapted paradigm of Solomon Asch. Results indicate that LA participants adapted to the incorrect group opinion more often than HA participants (42% vs. 30% of the trials, respectively). LA participants showed a larger posterior P1 component contralateral to targets presented in the right visual field when conforming to the correct compared to conforming to the incorrect group decision. In conclusion, our ERP data suggest that the group context can have early effects on our perception rather than on conscious decision processes in LA, but not HA participants.

  3. 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

  4. Emergent Group Level Navigation: An Agent-Based Evaluation of Movement Patterns in a Folivorous Primate

    PubMed Central

    Bonnell, Tyler R.; Campennì, Marco; Chapman, Colin A.; Gogarten, Jan F.; Reyna-Hurtado, Rafael A.; Teichroeb, Julie A.; Wasserman, Michael D.; Sengupta, Raja

    2013-01-01

    The foraging activity of many organisms reveal strategic movement patterns, showing efficient use of spatially distributed resources. The underlying mechanisms behind these movement patterns, such as the use of spatial memory, are topics of considerable debate. To augment existing evidence of spatial memory use in primates, we generated movement patterns from simulated primate agents with simple sensory and behavioral capabilities. We developed agents representing various hypotheses of memory use, and compared the movement patterns of simulated groups to those of an observed group of red colobus monkeys (Procolobus rufomitratus), testing for: the effects of memory type (Euclidian or landmark based), amount of memory retention, and the effects of social rules in making foraging choices at the scale of the group (independent or leader led). Our results indicate that red colobus movement patterns fit best with simulated groups that have landmark based memory and a follow the leader foraging strategy. Comparisons between simulated agents revealed that social rules had the greatest impact on a group’s step length, whereas the type of memory had the highest impact on a group’s path tortuosity and cohesion. Using simulation studies as experimental trials to test theories of spatial memory use allows the development of insight into the behavioral mechanisms behind animal movement, developing case-specific results, as well as general results informing how changes to perception and behavior influence movement patterns. PMID:24205174

  5. Emergent group level navigation: an agent-based evaluation of movement patterns in a folivorous primate.

    PubMed

    Bonnell, Tyler R; Campennì, Marco; Chapman, Colin A; Gogarten, Jan F; Reyna-Hurtado, Rafael A; Teichroeb, Julie A; Wasserman, Michael D; Sengupta, Raja

    2013-01-01

    The foraging activity of many organisms reveal strategic movement patterns, showing efficient use of spatially distributed resources. The underlying mechanisms behind these movement patterns, such as the use of spatial memory, are topics of considerable debate. To augment existing evidence of spatial memory use in primates, we generated movement patterns from simulated primate agents with simple sensory and behavioral capabilities. We developed agents representing various hypotheses of memory use, and compared the movement patterns of simulated groups to those of an observed group of red colobus monkeys (Procolobus rufomitratus), testing for: the effects of memory type (Euclidian or landmark based), amount of memory retention, and the effects of social rules in making foraging choices at the scale of the group (independent or leader led). Our results indicate that red colobus movement patterns fit best with simulated groups that have landmark based memory and a follow the leader foraging strategy. Comparisons between simulated agents revealed that social rules had the greatest impact on a group's step length, whereas the type of memory had the highest impact on a group's path tortuosity and cohesion. Using simulation studies as experimental trials to test theories of spatial memory use allows the development of insight into the behavioral mechanisms behind animal movement, developing case-specific results, as well as general results informing how changes to perception and behavior influence movement patterns.

  6. 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

  7. 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.

  8. Exploring Naval Tactics with UAVs in an Island Complex Using Agent-Based Simulation

    DTIC Science & Technology

    2007-06-01

    75 % Estealth 0-75 Enemy’s “next waypoint” 50-100 Enextwp 50-100 Enemy’s “cover” 0-100 Ecover 0-100 24 One of the most important issues for...20 30 Esensor 35 79 12 16 Estealth 0 20 40 60 Enextw p 5060 80 100 Ecover 20 50 80 Scatterplot Matrix Figure 16. Scatterplot matrix for the...screening experiment TOT Uspeed Usensor Ustealth Unextwp Uprocess Espeed Esensor Estealth Enextwp Ecover TOT 1 Uspeed -0.00734 1

  9. Promoting Conceptual Change for Complex Systems Understanding: Outcomes of an Agent-Based Participatory Simulation

    ERIC Educational Resources Information Center

    Rates, Christopher A.; Mulvey, Bridget K.; Feldon, David F.

    2016-01-01

    Components of complex systems apply across multiple subject areas, and teaching these components may help students build unifying conceptual links. Students, however, often have difficulty learning these components, and limited research exists to understand what types of interventions may best help improve understanding. We investigated 32 high…

  10. A Scaffolding Framework to Support Learning of Emergent Phenomena Using Multi-Agent-Based Simulation Environments

    ERIC Educational Resources Information Center

    Basu, Satabdi; Sengupta, Pratim; Biswas, Gautam

    2015-01-01

    Students from middle school to college have difficulties in interpreting and understanding complex systems such as ecological phenomena. Researchers have suggested that students experience difficulties in reconciling the relationships between individuals, populations, and species, as well as the interactions between organisms and their environment…

  11. An Agent-Based Model for Navigation Simulation in a Heterogeneous Environment

    ERIC Educational Resources Information Center

    Shanklin, Teresa A.

    2012-01-01

    Complex navigation (e.g. indoor and outdoor environments) can be studied as a system-of-systems problem. The model is made up of disparate systems that can aid a user in navigating from one location to another, utilizing whatever sensor system or information is available. By using intelligent navigation sensors and techniques (e.g. RFID, Wifi,…

  12. Exitus: An Agent-Based Evacuation Simulation Model for Heterogeneous Populations

    ERIC Educational Resources Information Center

    Manley, Matthew T.

    2012-01-01

    Evacuation planning for private-sector organizations is an important consideration given the continuing occurrence of both natural and human-caused disasters that inordinately affect them. Unfortunately, the traditional management approach that is focused on fire drills presents several practical challenges at the scale required for many…

  13. Agent-Based Simulation and Analysis of a Defensive UAV Swarm Against an Enemy UAV Swarm

    DTIC Science & Technology

    2011-06-01

    Monterey, California 9. CPT. Francisco J. Hederra Direccion de Investigacion , Programas y Desarrollo de la Armada Armada de Chile CHILE 10. CAPT Jeffrey Kline, USN(ret.) Naval Postgraduate School Monterey, California 91

  14. How Does Emotion Influence Collaboration? - An Agent Based Simulation of the Dynamic of Confrontation

    DTIC Science & Technology

    2011-08-01

    Springer.  Masters, R. (2000). Compassionate Wrath:  Transpersonal  Approaches to Anger.  The Journal of  Transpersonal   Psychology  , 32 (1), 31‐51.  Maulana...political  science,  psychology ,  organizational behavior, decision sciences, operations research and mathematics  (Sycara & Dai, 2010).   In  general...part of  psychology ,  neuroscience, and, more recently, artificial intelligence.  Current research on the neural circuitry of emotion suggests that

  15. Detection and Tracking Based on a Dynamical Hierarchical Occupancy Map in Agent-Based Simulations

    DTIC Science & Technology

    2008-09-01

    called pold . The new p(v) is the sum of the new incoming probability and the outgoing probability to the next nodes. Each edge from one node to...Output: Graph G’ For every active vertex v of G’ Copy p(v) in pold (v) For every edge E outgoing Get target node v’ p(v’) = p(v’) + (1...cost of E)* pold (v) p(v) = p(v) – (1/cost of E)* pold (v) 36 values are too small to make a reasonable search process. Therefore, there must be

  16. 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

  17. The Use of Agent Based Simulation for Cooperative Sensing of the Battlefield

    DTIC Science & Technology

    2005-12-01

    ChiSquare ...122 128 6 DF 104.84869 232.26793 337.11662 -LogLikelihood 209.6974 ChiSquare <.0001 Prob>ChiSq Lack Of Fit Intercept LAE React InOrg SA... ChiSquare <.0001 0.0027 <.0001 <.0001 <.0001 <.0001 <.0001 Prob>ChiSq For log odds of 0/1 Parameter Estimates Nominal Logistic Fit for Low TCT Class

  18. 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%.

  19. 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.

  20. 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.

  1. 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

  2. Simulating social-ecological systems: the Island Digital Ecosystem Avatars (IDEA) consortium.

    PubMed

    Davies, Neil; Field, Dawn; Gavaghan, David; Holbrook, Sally J; Planes, Serge; Troyer, Matthias; Bonsall, Michael; Claudet, Joachim; Roderick, George; Schmitt, Russell J; Zettler, Linda Amaral; Berteaux, Véronique; Bossin, Hervé C; Cabasse, Charlotte; Collin, Antoine; Deck, John; Dell, Tony; Dunne, Jennifer; Gates, Ruth; Harfoot, Mike; Hench, James L; Hopuare, Marania; Kirch, Patrick; Kotoulas, Georgios; Kosenkov, Alex; Kusenko, Alex; Leichter, James J; Lenihan, Hunter; Magoulas, Antonios; Martinez, Neo; Meyer, Chris; Stoll, Benoit; Swalla, Billie; Tartakovsky, Daniel M; Murphy, Hinano Teavai; Turyshev, Slava; Valdvinos, Fernanda; Williams, Rich; Wood, Spencer

    2016-01-01

    Systems biology promises to revolutionize medicine, yet human wellbeing is also inherently linked to healthy societies and environments (sustainability). The IDEA Consortium is a systems ecology open science initiative to conduct the basic scientific research needed to build use-oriented simulations (avatars) of entire social-ecological systems. Islands are the most scientifically tractable places for these studies and we begin with one of the best known: Moorea, French Polynesia. The Moorea IDEA will be a sustainability simulator modeling links and feedbacks between climate, environment, biodiversity, and human activities across a coupled marine-terrestrial landscape. As a model system, the resulting knowledge and tools will improve our ability to predict human and natural change on Moorea and elsewhere at scales relevant to management/conservation actions.

  3. 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

  4. 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.

  5. 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

  6. 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

  7. Agent-based model forecasts aging of the population of people who inject drugs in metropolitan Chicago and changing prevalence of hepatitis C infections

    DOE PAGES

    Gutfraind, Alexander; Boodram, Basmattee; Prachand, Nikhil; ...

    2015-09-30

    People who inject drugs (PWID) are at high risk for blood-borne pathogens transmitted during the sharing of contaminated injection equipment, particularly hepatitis C virus (HCV). HCV prevalence is influenced by a complex interplay of drug-use behaviors, social networks, and geography, as well as the availability of interventions, such as needle exchange programs. To adequately address this complexity in HCV epidemic forecasting, we have developed a computational model, the Agent-based Pathogen Kinetics model (APK). APK simulates the PWID population in metropolitan Chicago, including the social interactions that result in HCV infection. We used multiple empirical data sources on Chicago PWID tomore » build a spatial distribution of an in silico PWID population and modeled networks among the PWID by considering the geography of the city and its suburbs. APK was validated against 2012 empirical data (the latest available) and shown to agree with network and epidemiological surveys to within 1%. For the period 2010–2020, APK forecasts a decline in HCV prevalence of 0.8% per year from 44(±2)% to 36(±5)%, although some sub-populations would continue to have relatively high prevalence, including Non-Hispanic Blacks, 48(±5)%. The rate of decline will be lowest in Non-Hispanic Whites and we find, in a reversal of historical trends, that incidence among non-Hispanic Whites would exceed incidence among Non-Hispanic Blacks (0.66 per 100 per years vs 0.17 per 100 person years). APK also forecasts an increase in PWID mean age from 35(±1) to 40(±2) with a corresponding increase from 59(±2)% to 80(±6)% in the proportion of the population >30 years old. Our research highlight the importance of analyzing sub-populations in disease predictions, the utility of computer simulation for analyzing demographic and health trends among PWID and serve as a tool for guiding intervention and prevention strategies in Chicago, and other major cities.« less

  8. Agent-based model forecasts aging of the population of people who inject drugs in metropolitan Chicago and changing prevalence of hepatitis C infections

    SciTech Connect

    Gutfraind, Alexander; Boodram, Basmattee; Prachand, Nikhil; Hailegiorgis, Atesmachew; Dahari, Harel; Major, Marian E.; Kaderali, Lars

    2015-09-30

    People who inject drugs (PWID) are at high risk for blood-borne pathogens transmitted during the sharing of contaminated injection equipment, particularly hepatitis C virus (HCV). HCV prevalence is influenced by a complex interplay of drug-use behaviors, social networks, and geography, as well as the availability of interventions, such as needle exchange programs. To adequately address this complexity in HCV epidemic forecasting, we have developed a computational model, the Agent-based Pathogen Kinetics model (APK). APK simulates the PWID population in metropolitan Chicago, including the social interactions that result in HCV infection. We used multiple empirical data sources on Chicago PWID to build a spatial distribution of an in silico PWID population and modeled networks among the PWID by considering the geography of the city and its suburbs. APK was validated against 2012 empirical data (the latest available) and shown to agree with network and epidemiological surveys to within 1%. For the period 2010–2020, APK forecasts a decline in HCV prevalence of 0.8% per year from 44(±2)% to 36(±5)%, although some sub-populations would continue to have relatively high prevalence, including Non-Hispanic Blacks, 48(±5)%. The rate of decline will be lowest in Non-Hispanic Whites and we find, in a reversal of historical trends, that incidence among non-Hispanic Whites would exceed incidence among Non-Hispanic Blacks (0.66 per 100 per years vs 0.17 per 100 person years). APK also forecasts an increase in PWID mean age from 35(±1) to 40(±2) with a corresponding increase from 59(±2)% to 80(±6)% in the proportion of the population >30 years old. Our research highlight the importance of analyzing sub-populations in disease predictions, the utility of computer simulation for analyzing demographic and health trends among PWID and serve as a tool for guiding intervention and prevention strategies in Chicago, and other major cities.

  9. Reducing complexity in an agent based reaction model-Benefits and limitations of simplifications in relation to run time and system level output.

    PubMed

    Rhodes, David M; Holcombe, Mike; Qwarnstrom, Eva E

    2016-09-01

    Agent based modelling is a methodology for simulating a variety of systems across a broad spectrum of fields. However, due to the complexity of the systems it is often impossible or impractical to model them at a one to one scale. In this paper we use a simple reaction rate model implemented using the FLAME framework to test the impact of common methods for reducing model complexity such as reducing scale, increasing iteration duration and reducing message overheads. We demonstrate that such approaches can have significant impact on simulation runtime albeit with increasing risk of aberrant system behaviour and errors, as the complexity of the model is reduced.

  10. Towards a living earth simulator

    NASA Astrophysics Data System (ADS)

    Paolucci, M.; Kossman, D.; Conte, R.; Lukowicz, P.; Argyrakis, P.; Blandford, A.; Bonelli, G.; Anderson, S.; de Freitas, S.; Edmonds, B.; Gilbert, N.; Gross, M.; Kohlhammer, J.; Koumoutsakos, P.; Krause, A.; Linnér, B.-O.; Slusallek, P.; Sorkine, O.; Sumner, R. W.; Helbing, D.

    2012-11-01

    The Living Earth Simulator (LES) is one of the core components of the FuturICT architecture. It will work as a federation of methods, tools, techniques and facilities supporting all of the FuturICT simulation-related activities to allow and encourage interactive exploration and understanding of societal issues. Society-relevant problems will be targeted by leaning on approaches based on complex systems theories and data science in tight interaction with the other components of FuturICT. The LES will evaluate and provide answers to real-world questions by taking into account multiple scenarios. It will build on present approaches such as agent-based simulation and modeling, multiscale modelling, statistical inference, and data mining, moving beyond disciplinary borders to achieve a new perspective on complex social systems.

  11. 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…

  12. 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.

  13. Using Agent-Based Technologies to Enhance Learning in Educational Games

    ERIC Educational Resources Information Center

    Tumenayu, Ogar Ofut; Shabalina, Olga; Kamaev, Valeriy; Davtyan, Alexander

    2014-01-01

    Recent research has shown that educational games positively motivate learning. However, there is a little evidence that they can trigger learning to a large extent if the game-play is supported by additional activities. We aim to support educational games development with an Agent-Based Technology (ABT) by using intelligent pedagogical agents that…

  14. The Impact of a Peer-Learning Agent Based on Pair Programming in a Programming Course

    ERIC Educational Resources Information Center

    Han, Keun-Woo; Lee, EunKyoung; Lee, YoungJun

    2010-01-01

    This paper analyzes the educational effects of a peer-learning agent based on pair programming in programming courses. A peer-learning agent system was developed to facilitate the learning of a programming language through the use of pair programming strategies. This system is based on the role of a peer-learning agent from pedagogical and…

  15. Developing an Argument Learning Environment Using Agent-Based ITS (ALES)

    ERIC Educational Resources Information Center

    Abbas, Safia; Sawamura, Hajime

    2009-01-01

    This paper presents an agent-based educational environment to teach argument analysis (ALES). The idea is based on the Argumentation Interchange Format Ontology (AIF)using "Walton Theory". ALES uses different mining techniques to manage a highly structured arguments repertoire. This repertoire was designed, developed and implemented by us. Our aim…

  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. Agent-Based Learning Environments as a Research Tool for Investigating Teaching and Learning.

    ERIC Educational Resources Information Center

    Baylor, Amy L.

    2002-01-01

    Discusses intelligent learning environments for computer-based learning, such as agent-based learning environments, and their advantages over human-based instruction. Considers the effects of multiple agents; agents and research design; the use of Multiple Intelligent Mentors Instructing Collaboratively (MIMIC) for instructional design for…

  18. Permutations of Control: Cognitive Considerations for Agent-Based Learning Environments

    ERIC Educational Resources Information Center

    Baylor, Amy L.

    2004-01-01

    While there has been a significant amount of research on technical issues regarding the development of agent-based learning environments (e.g., see the special issue of Journal of "Interactive Learning Research," 10(3/4)), there is less information regarding cognitive foundations for these environments. The management of control is a prime issue…

  19. Permutations of Control: Cognitive Considerations for Agent-Based Learning Environments.

    ERIC Educational Resources Information Center

    Baylor, Amy L.

    2001-01-01

    Discussion of intelligent agents and their use in computer learning environments focuses on cognitive considerations. Presents four dimension of control that should be considered in designing agent-based learning environments: learner control, from constructivist to instructivist; feedback; relationship of learner to agent; and learner confidence…

  20. Efficacy and Safety of Novel Agent-Based Therapies for Multiple Myeloma: A Meta-Analysis

    PubMed Central

    Wang, Xiaoxue; Li, Yan; Yan, Xiaojing

    2016-01-01

    This study aimed at comparing bortezomib, thalidomide, and lenalidomide in patients with multiple myeloma (MM) for safety and efficacy using meta-analysis. This meta-analysis identified 17 randomized controlled trials (RCTs) including 6742 patients. These RCTs were separated according to the different agent-based regimens and to autologous stem-cell transplantation (ASCT). Complete response (CR), progression-free survival (PFS), overall survival (OS), and adverse events (AE) were combined. The total weighted risk ratio (RR) of CR was 3.29 [95% confidence interval (95% CI): 2.22–4.88] (P < 0.0001) for the novel agent-based regimens. These novel agent-based regimens showed greater benefit in terms of PFS of all subgroups irrespective of whether the patient received ASCT or not. The hazard ratio (HR) for PFS was 0.64 [95% CI: 0.60–0.69] (P < 0.00001). Improvements of OS could be found only in the bortezomib- and thalidomide-based regimens without ASCT. The pooled HRs were 0.74 [95% CI: 0.65–0.86] (P < 0.0001) and 0.80 [95% CI: 0.70–0.90] (P = 0.0004), respectively. Several AEs were shown more frequently in the novel agent-based regimens compared with controls such as hematologic events (neutropenia, anemia, and thrombocytopenia), gastrointestinal infection, peripheral neuropathy, thrombosis, and embolism events. In conclusion, in spite of the AEs, novel agent-based regimens are safe and effective for the treatment of MM. PMID:26949704

  1. Sensitivity Analysis in Agent-Based Models of Socio-Ecological Systems: An Example in Agricultural Land Conservation for Lake Water Quality Improvement

    NASA Astrophysics Data System (ADS)

    Ligmann-Zielinska, A.; Kramer, D. B.; Spence Cheruvelil, K.; Soranno, P.

    2012-12-01

    Socio-ecological systems are dynamic and nonlinear. To account for this complexity, we employ agent-based models (ABMs) to study macro-scale phenomena resulting from micro-scale interactions among system components. Because ABMs typically have many parameters, it is challenging to identify which parameters contribute to the emerging macro-scale patterns. In this paper, we address the following question: What is the extent of participation in agricultural land conservation programs given heterogeneous landscape, economic, social, and individual decision making criteria in complex lakesheds? To answer this question, we: [1] built an ABM for our model system; [2] simulated land use change resulting from agent decision making, [3] estimated the uncertainty of the model output, decomposed it and apportioned it to each of the parameters in the model. Our model system is a freshwater socio-ecological system - that of farmland and lake water quality within a region containing a large number of lakes and high proportions of agricultural lands. Our study focuses on examining how agricultural land conversion from active to fallow reduces freshwater nutrient loading and improves water quality. Consequently, our ABM is composed of farmer agents who make decisions related to participation in a government-sponsored Conservation Reserve Program (CRP) managed by the Farm Service Agency (FSA). We also include an FSA agent, who selects enrollment offers made by farmers and announces the signup results leading to land use change. The model is executed in a Monte Carlo simulation framework to generate a distribution of maps of fallow lands that are used for calculating nutrient loading to lakes. What follows is a variance-based sensitivity analysis of the results. We compute sensitivity indices for individual parameters and their combinations, allowing for identification of the most influential as well as the insignificant inputs. In the case study, we observe that farmland

  2. Proactive monitoring and adaptive management of social carrying capacity in Arches National Park: an application of computer simulation modeling.

    PubMed

    Lawson, Steven R; Manning, Robert E; Valliere, William A; Wang, Benjamin

    2003-07-01

    Public visits to parks and protected areas continue to increase and may threaten the integrity of natural and cultural resources and the quality of the visitor experience. Scientists and managers have adopted the concept of carrying capacity to address the impacts of visitor use. In the context of outdoor recreation, the social component of carrying capacity refers to the level of visitor use that can be accommodated in parks and protected areas without diminishing the quality of the visitor experience to an unacceptable degree. This study expands and illustrates the use of computer simulation modeling as a tool for proactive monitoring and adaptive management of social carrying capacity at Arches National Park. A travel simulation model of daily visitor use throughout the Park's road and trail network and at selected attraction sites was developed, and simulations were conducted to estimate a daily social carrying capacity for Delicate Arch, an attraction site in Arches National Park, and for the Park as a whole. Further, a series of simulations were conducted to estimate the effect of a mandatory shuttle bus system on daily social carrying capacity of Delicate Arch to illustrate how computer simulation modeling can be used as a tool to facilitate adaptive management of social carrying capacity.

  3. 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

  4. Agent-Based Model of Human Alveoli Predicts Chemotactic Signaling by Epithelial Cells during Early Aspergillus fumigatus Infection

    PubMed Central

    Pollmächer, Johannes; Figge, Marc Thilo

    2014-01-01

    Aspergillus fumigatus is one of the most important human fungal pathogens, causing life-threatening diseases. Since humans inhale hundreds to thousands of fungal conidia every day, the lower respiratory tract is the primary site of infection. Current interaction networks of the innate immune response attribute fungal recognition and detection to alveolar macrophages, which are thought to be the first cells to get in contact with the fungus. At present, these networks are derived from in vitro or in situ assays, as the peculiar physiology of the human lung makes in vivo experiments, including imaging on the cell-level, hard to realize. We implemented a spatio-temporal agent-based model of a human alveolus in order to perform in silico experiments of a virtual infection scenario, for an alveolus infected with A. fumigatus under physiological conditions. The virtual analog captures the three-dimensional alveolar morphology consisting of the two major alveolar epithelial cell types and the pores of Kohn as well as the dynamic process of respiration. To the best of our knowledge this is the first agent-based model of a dynamic human alveolus in the presence of respiration. A key readout of our simulations is the first-passage-time of alveolar macrophages, which is the period of time that elapses until the first physical macrophage-conidium contact is established. We tested for random and chemotactic migration modes of alveolar macrophages and varied their corresponding parameter sets. The resulting first-passage-time distributions imply that randomly migrating macrophages fail to find the conidium before the start of germination, whereas guidance by chemotactic signals derived from the alveolar epithelial cell associated with the fungus enables a secure and successful discovery of the pathogen in time. PMID:25360787

  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. Use of agent-based modeling to explore the mechanisms of intracellular phosphorus heterogeneity in cultured phytoplankton.

    PubMed

    Fredrick, Neil D; Berges, John A; Twining, Benjamin S; Nuñez-Milland, Daliangelis; Hellweger, Ferdi L

    2013-07-01

    There can be significant intraspecific individual-level heterogeneity in the intracellular P of phytoplankton, which can affect the population-level growth rate. Several mechanisms can create this heterogeneity, including phenotypic variability in various physiological functions (e.g., nutrient uptake rate). Here, we use modeling to explore the contribution of various mechanisms to the heterogeneity in phytoplankton grown in a laboratory culture. An agent-based model simulates individual cells and their intracellular P. Heterogeneity is introduced by randomizing parameters (e.g., maximum uptake rate) of daughter cells at division. The model was calibrated to observations of the P quota of individual cells of the centric diatom Thalassiosira pseudonana, which were obtained using synchrotron X-ray fluorescence (SXRF). A number of simulations, with individual mechanisms of heterogeneity turned off, then were performed. Comparison of the coefficient of variation (CV) of these and the baseline simulation (i.e., all mechanisms turned on) provides an estimate of the relative contribution of these mechanisms. The results show that the mechanism with the largest contribution to variability is the parameter characterizing the maximum intracellular P, which, when removed, results in a CV of 0.21 compared to a CV of 0.37 with all mechanisms turned on. This suggests that nutrient/element storage capabilities/mechanisms are important determinants of intrapopulation heterogeneity.

  7. Towards modeling and simulation of integrated social and health care services for elderly.

    PubMed

    Horsch, Alexander; Khoshsima, Daryoush

    2007-01-01

    In order to estimate the impact of an innovation on a segment of the health care system under certain assumptions such as different possible regulatory or financing schemes (scenarios) prior to its diffusion, one must understand the dynamic behavior of the entire system with its essential control loops. Aim of this feasibility study was to explore the potential of System Dynamics (SD) modeling for this purpose. First, a UML-based modeling of an Innovative Care for Elderly (ICE) system for provision of integrated social and health care services to elderly living at home was done. Then monetary and quality of life aspects of the social and health care system were described by two coarse SD models. On these models the impact of the introduction of the ICE system under certain assumption (scenarios) was studied, based on data from the German Health Expenditure and German Federal Statistics Office. The simulations show plausible behavior, however, are not yet detailed enough for a final conclusion. A major problem is missing data for setting model parameters: estimates had to be made. In conclusion, SD modeling might be a useful method for studying impacts of the diffusion of an innovation in the health for elderly sector, but more research is needed.

  8. Proceedings 3rd NASA/IEEE Workshop on Formal Approaches to Agent-Based Systems (FAABS-III)

    NASA Technical Reports Server (NTRS)

    Hinchey, Michael (Editor); Rash, James (Editor); Truszkowski, Walt (Editor); Rouff, Christopher (Editor)

    2004-01-01

    These preceedings contain 18 papers and 4 poster presentation, covering topics such as: multi-agent systems, agent-based control, formalism, norms, as well as physical and biological models of agent-based systems. Some applications presented in the proceedings include systems analysis, software engineering, computer networks and robot control.

  9. 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.

  10. 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.

  11. Nonlinear multi-analysis of agent-based financial market dynamics by epidemic system.

    PubMed

    Lu, Yunfan; Wang, Jun; Niu, Hongli

    2015-10-01

    Based on the epidemic dynamical system, we construct a new agent-based financial time series model. In order to check and testify its rationality, we compare the statistical properties of the time series model with the real stock market indices, Shanghai Stock Exchange Composite Index and Shenzhen Stock Exchange Component Index. For analyzing the statistical properties, we combine the multi-parameter analysis with the tail distribution analysis, the modified rescaled range analysis, and the multifractal detrended fluctuation analysis. For a better perspective, the three-dimensional diagrams are used to present the analysis results. The empirical research in this paper indicates that the long-range dependence property and the multifractal phenomenon exist in the real returns and the proposed model. Therefore, the new agent-based financial model can recurrence some important features of real stock markets.

  12. Nonlinear multi-analysis of agent-based financial market dynamics by epidemic system

    NASA Astrophysics Data System (ADS)

    Lu, Yunfan; Wang, Jun; Niu, Hongli

    2015-10-01

    Based on the epidemic dynamical system, we construct a new agent-based financial time series model. In order to check and testify its rationality, we compare the statistical properties of the time series model with the real stock market indices, Shanghai Stock Exchange Composite Index and Shenzhen Stock Exchange Component Index. For analyzing the statistical properties, we combine the multi-parameter analysis with the tail distribution analysis, the modified rescaled range analysis, and the multifractal detrended fluctuation analysis. For a better perspective, the three-dimensional diagrams are used to present the analysis results. The empirical research in this paper indicates that the long-range dependence property and the multifractal phenomenon exist in the real returns and the proposed model. Therefore, the new agent-based financial model can recurrence some important features of real stock markets.

  13. 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.

  14. 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.

  15. Preclinical animal acute toxicity studies of new developed MRI contrast agent based on gadolinium

    NASA Astrophysics Data System (ADS)

    Nam, I. F.; Zhuk, V. V.

    2015-04-01

    Acute toxicity test of new developed MRI contrast agent based on disodium salt of gadopentetic acid complex were carried out on Mus musculus and Sprague Dawley rats according to guidelines of preclinical studies [1]. Groups of six animals each were selected for experiment. Death and clinical symptoms of animals were recorded during 14 days. As a result the maximum tolerated dose (MTD) for female mice is 2.8 mM/kg of body weight, male mice - 1.4 mM/kg, female rats - 2.8 mM/kg, male rats - 5.6 mM/kg of body weight. No Observed Adverse Effect Dose (NOAEL) for female mice is 1.4 mM/kg, male mice - 0.7 mM/kg, male and female rats - 0.7 mM/kg. According to experimental data new developed MRI contrast agent based on Gd-DTPA complex is low-toxic.

  16. Sociality, selection, and survival: simulated evolution of mortality with intergenerational transfers and food sharing.

    PubMed

    Lee, Ronald

    2008-05-20

    Why do humans survive so long past reproductive age, and why does juvenile mortality decline after birth, both contrary to the classic theory of aging? Previous work has shown formally that intergenerational transfers can explain both these patterns. Here, simulations confirm those results under weaker assumptions and explore how different social arrangements shape life-history evolution. Simulated single-sex hunter-gatherers survive, forage, reproduce, and share food with kin and nonkin in ways guided by the ethnographic literature. Natural selection acts on probabilistically occurring deleterious mutations. Neither stable population age distributions nor homogeneous genetic lineages are assumed. When food is shared only within kin groups, an infant death permits reallocation of its unneeded food to the infant's kin, offsetting the fitness cost of the death and weakening the force of selection against infant mortality. Thus, evolved infant mortality is relatively high, more so in larger kin groups. Food sharing with nonkin reduces the costs to kin of child rearing, but also reduces the resources recaptured by kin after an infant death, so evolved infant mortality is lower. Postreproductive adults transfer food to descendants, enhancing their growth and survival, so postreproductive survival is selected. The force of selection for old-age survival depends in complicated ways on the food-sharing arrangements. Population-level food sharing with nonkin leads to the classic pattern of constant low mortality up to sexual maturity and no postreproductive survival.

  17. 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.

  18. 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.

  19. 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.

  20. Intelligent Agent Feasibility Study. Volume 1: Agent-based System Technology

    DTIC Science & Technology

    1998-02-01

    ambitious in its scope. In OAA (Moran, Cheyer, Julia , Martin, 10 & Park, 1997), agents can operate on multiple platforms across a network, new agents can be...find the source and best price for a given item. This area of electronic commerce has been an active area for research in agent-based systems ( Chavez ...D. (1993). Towards a taxonomy of multi-agent systems. International Journal of Man-Machine Studies 36, 689-704. Chavez , A., Dreilinger, D., Guttman, R