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

PubMed

Laghari, Samreen; Niazi, Muaz A

2016-01-01

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

Ecology Based Decentralized Agent Management System

NASA Technical Reports Server (NTRS)

Peysakhov, Maxim D.; Cicirello, Vincent A.; Regli, William C.

2004-01-01

The problem of maintaining a desired number of mobile agents on a network is not trivial, especially if we want a completely decentralized solution. Decentralized control makes a system more r e bust and less susceptible to partial failures. The problem is exacerbated on wireless ad hoc networks where host mobility can result in significant changes in the network size and topology. In this paper we propose an ecology-inspired approach to the management of the number of agents. The approach associates agents with living organisms and tasks with food. Agents procreate or die based on the abundance of uncompleted tasks (food). We performed a series of experiments investigating properties of such systems and analyzed their stability under various conditions. We concluded that the ecology based metaphor can be successfully applied to the management of agent populations on wireless ad hoc networks.

A New Approach To Secure Federated Information Bases Using Agent Technology.

ERIC Educational Resources Information Center

Weippi, Edgar; Klug, Ludwig; Essmayr, Wolfgang

2003-01-01

Discusses database agents which can be used to establish federated information bases by integrating heterogeneous databases. Highlights include characteristics of federated information bases, including incompatible database management systems, schemata, and frequently changing context; software agent technology; Java agents; system architecture;…

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

Efficient Agent-Based Cluster Ensembles

NASA Technical Reports Server (NTRS)

Agogino, Adrian; Tumer, Kagan

2006-01-01

Numerous domains ranging from distributed data acquisition to knowledge reuse need to solve the cluster ensemble problem of combining multiple clusterings into a single unified clustering. Unfortunately current non-agent-based cluster combining methods do not work in a distributed environment, are not robust to corrupted clusterings and require centralized access to all original clusterings. Overcoming these issues will allow cluster ensembles to be used in fundamentally distributed and failure-prone domains such as data acquisition from satellite constellations, in addition to domains demanding confidentiality such as combining clusterings of user profiles. This paper proposes an efficient, distributed, agent-based clustering ensemble method that addresses these issues. In this approach each agent is assigned a small subset of the data and votes on which final cluster its data points should belong to. The final clustering is then evaluated by a global utility, computed in a distributed way. This clustering is also evaluated using an agent-specific utility that is shown to be easier for the agents to maximize. Results show that agents using the agent-specific utility can achieve better performance than traditional non-agent based methods and are effective even when up to 50% of the agents fail.

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.

The practice of agent-based model visualization.

PubMed

Dorin, Alan; Geard, Nicholas

2014-01-01

We discuss approaches to agent-based model visualization. Agent-based modeling has its own requirements for visualization, some shared with other forms of simulation software, and some unique to this approach. In particular, agent-based models are typified by complexity, dynamism, nonequilibrium and transient behavior, heterogeneity, and a researcher's interest in both individual- and aggregate-level behavior. These are all traits requiring careful consideration in the design, experimentation, and communication of results. In the case of all but final communication for dissemination, researchers may not make their visualizations public. Hence, the knowledge of how to visualize during these earlier stages is unavailable to the research community in a readily accessible form. Here we explore means by which all phases of agent-based modeling can benefit from visualization, and we provide examples from the available literature and online sources to illustrate key stages and techniques.

A Scalable and Robust Multi-Agent Approach to Distributed Optimization

NASA Technical Reports Server (NTRS)

Tumer, Kagan

2005-01-01

Modularizing a large optimization problem so that the solutions to the subproblems provide a good overall solution is a challenging problem. In this paper we present a multi-agent approach to this problem based on aligning the agent objectives with the system objectives, obviating the need to impose external mechanisms to achieve collaboration among the agents. This approach naturally addresses scaling and robustness issues by ensuring that the agents do not rely on the reliable operation of other agents We test this approach in the difficult distributed optimization problem of imperfect device subset selection [Challet and Johnson, 2002]. In this problem, there are n devices, each of which has a "distortion", and the task is to find the subset of those n devices that minimizes the average distortion. Our results show that in large systems (1000 agents) the proposed approach provides improvements of over an order of magnitude over both traditional optimization methods and traditional multi-agent methods. Furthermore, the results show that even in extreme cases of agent failures (i.e., half the agents fail midway through the simulation) the system remains coordinated and still outperforms a failure-free and centralized optimization algorithm.

Agent-Based Model Approach to Complex Phenomena in Real Economy

NASA Astrophysics Data System (ADS)

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

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

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

NASA Astrophysics Data System (ADS)

Alexandridis, Konstantinos T.

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

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.

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

Agent Based Fault Tolerance for the Mobile Environment

NASA Astrophysics Data System (ADS)

Park, Taesoon

This paper presents a fault-tolerance scheme based on mobile agents for the reliable mobile computing systems. Mobility of the agent is suitable to trace the mobile hosts and the intelligence of the agent makes it efficient to support the fault tolerance services. This paper presents two approaches to implement the mobile agent based fault tolerant service and their performances are evaluated and compared with other fault-tolerant schemes.

A practical approach for active camera coordination based on a fusion-driven multi-agent system

NASA Astrophysics Data System (ADS)

Bustamante, Alvaro Luis; Molina, José M.; Patricio, Miguel A.

2014-04-01

In this paper, we propose a multi-agent system architecture to manage spatially distributed active (or pan-tilt-zoom) cameras. Traditional video surveillance algorithms are of no use for active cameras, and we have to look at different approaches. Such multi-sensor surveillance systems have to be designed to solve two related problems: data fusion and coordinated sensor-task management. Generally, architectures proposed for the coordinated operation of multiple cameras are based on the centralisation of management decisions at the fusion centre. However, the existence of intelligent sensors capable of decision making brings with it the possibility of conceiving alternative decentralised architectures. This problem is approached by means of a MAS, integrating data fusion as an integral part of the architecture for distributed coordination purposes. This paper presents the MAS architecture and system agents.

Comparing administered and market-based water allocation systems using an agent-based modeling approach

NASA Astrophysics Data System (ADS)

Zhao, J.; Cai, X.; Wang, Z.

2009-12-01

It also has been well recognized that market-based systems can have significant advantages over administered systems for water allocation. However there are not many successful water markets around the world yet and administered systems exist commonly in water allocation management practice. This paradox has been under discussion for decades and still calls for attention for both research and practice. This paper explores some insights for the paradox and tries to address why market systems have not been widely implemented for water allocation. Adopting the theory of agent-based system we develop a consistent analytical model to interpret both systems. First we derive some theorems based on the analytical model, with respect to the necessary conditions for economic efficiency of water allocation. Following that the agent-based model is used to illustrate the coherence and difference between administered and market-based systems. The two systems are compared from three aspects: 1) the driving forces acting on the system state, 2) system efficiency, and 3) equity. Regarding economic efficiency, penalty on the violation of water use permits (or rights) under an administered system can lead to system-wide economic efficiency, as well as being acceptable by some agents, which follows the theory of the so-call rational violation. Ideal equity will be realized if penalty equals incentive with an administered system and if transaction costs are zero with a market system. The performances of both agents and the over system are explained with an administered system and market system, respectively. The performances of agents are subject to different mechanisms of interactions between agents under the two systems. The system emergency (i.e., system benefit, equilibrium market price, etc), resulting from the performance at the agent level, reflects the different mechanism of the two systems, the “invisible hand” with the market system and administrative measures (penalty

An agent-based approach for modeling dynamics of contagious disease spread

PubMed Central

Perez, Liliana; Dragicevic, Suzana

2009-01-01

Background The propagation of communicable diseases through a population is an inherent spatial and temporal process of great importance for modern society. For this reason a spatially explicit epidemiologic model of infectious disease is proposed for a greater understanding of the disease's spatial diffusion through a network of human contacts. Objective The objective of this study is to develop an agent-based modelling approach the integrates geographic information systems (GIS) to simulate the spread of a communicable disease in an urban environment, as a result of individuals' interactions in a geospatial context. Methods The methodology for simulating spatiotemporal dynamics of communicable disease propagation is presented and the model is implemented using measles outbreak in an urban environment as a case study. Individuals in a closed population are explicitly represented by agents associated to places where they interact with other agents. They are endowed with mobility, through a transportation network allowing them to move between places within the urban environment, in order to represent the spatial heterogeneity and the complexity involved in infectious diseases diffusion. The model is implemented on georeferenced land use dataset from Metro Vancouver and makes use of census data sets from Statistics Canada for the municipality of Burnaby, BC, Canada study site. Results The results provide insights into the application of the model to calculate ratios of susceptible/infected in specific time frames and urban environments, due to its ability to depict the disease progression based on individuals' interactions. It is demonstrated that the dynamic spatial interactions within the population lead to high numbers of exposed individuals who perform stationary activities in areas after they have finished commuting. As a result, the sick individuals are concentrated in geographical locations like schools and universities. Conclusion The GIS-agent based model

How new concepts become universal scientific approaches: insights from citation network analysis of agent-based complex systems science.

PubMed

Vincenot, Christian E

2018-03-14

Progress in understanding and managing complex systems comprised of decision-making agents, such as cells, organisms, ecosystems or societies, is-like many scientific endeavours-limited by disciplinary boundaries. These boundaries, however, are moving and can actively be made porous or even disappear. To study this process, I advanced an original bibliometric approach based on network analysis to track and understand the development of the model-based science of agent-based complex systems (ACS). I analysed research citations between the two communities devoted to ACS research, namely agent-based (ABM) and individual-based modelling (IBM). Both terms refer to the same approach, yet the former is preferred in engineering and social sciences, while the latter prevails in natural sciences. This situation provided a unique case study for grasping how a new concept evolves distinctly across scientific domains and how to foster convergence into a universal scientific approach. The present analysis based on novel hetero-citation metrics revealed the historical development of ABM and IBM, confirmed their past disjointedness, and detected their progressive merger. The separation between these synonymous disciplines had silently opposed the free flow of knowledge among ACS practitioners and thereby hindered the transfer of methodological advances and the emergence of general systems theories. A surprisingly small number of key publications sparked the ongoing fusion between ABM and IBM research. Beside reviews raising awareness of broad-spectrum issues, generic protocols for model formulation and boundary-transcending inference strategies were critical means of science integration. Accessible broad-spectrum software similarly contributed to this change. From the modelling viewpoint, the discovery of the unification of ABM and IBM demonstrates that a wide variety of systems substantiate the premise of ACS research that microscale behaviours of agents and system-level dynamics

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…

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…

Global critical materials markets: An agent-based modeling approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Riddle, Matthew; Macal, Charles M.; Conzelmann, Guenter

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

A patient-centred approach to treatment with incretin-based agents in patients with type 2 diabetes.

PubMed

Cornell, Susan A

2013-06-01

The 2012 position statement from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) recommends a haemoglobin A1c level of <7% for most patients with type 2 diabetes (T2D). Initial therapy consists of lifestyle changes plus metformin, with an emphasis on a patient-centred approach to management. Addition of incretin-based therapy is recommended as an add-on after metformin failure, and later on in combination with basal insulin. Basal insulin is recommended from the onset in patients with A1c ≥10%. The possibility of incorporating incretin-based therapy in the patient-centred approach will be investigated both in the literature and clinical experience. Incretin-based therapy targets multiple dysfunctional organ systems in T2D and provides sustained glycaemic control, with extraglycaemic benefits and low risk of hypoglycaemia. To initiate an incretin-based therapy that best fits an individual patient's needs, the patient's A1c level, preference and comorbid conditions should be considered along with any drug safety and adherence-related issues. There is good evidence to support the patient-centred approach to T2D management. This approach allows patient treatment goals and personal preferences to be matched with the clinical profile(s) of one or more agents to formulate a treatment plan that can best achieve the goals. Incretin-based therapies are an important class of agents to consider after metformin monotherapy failure and later in combination with basal insulin. By matching patient needs with the clinical profiles of the various treatment options, pharmacists can actively engage in the practice of patient-centred care and management. © 2013 Blackwell Publishing Ltd.

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

An Agent-Based Modeling Approach for Determining Corn Stover Removal Rate and Transboundary Effects

NASA Astrophysics Data System (ADS)

Gan, Jianbang; Langeveld, J. W. A.; Smith, C. T.

2014-02-01

Bioenergy production involves different agents with potentially different objectives, and an agent's decision often has transboundary impacts on other agents along the bioenergy value chain. Understanding and estimating the transboundary impacts is essential to portraying the interactions among the different agents and in the search for the optimal configuration of the bioenergy value chain. We develop an agent-based model to mimic the decision making by feedstock producers and feedstock-to-biofuel conversion plant operators and propose multipliers (i.e., ratios of economic values accruing to different segments and associated agents in the value chain) for assessing the transboundary impacts. Our approach is generic and thus applicable to a variety of bioenergy production systems at different sites and geographic scales. We apply it to the case of producing ethanol using corn stover in Iowa, USA. The results from the case study indicate that stover removal rate is site specific and varies considerably with soil type, as well as other factors, such as stover price and harvesting cost. In addition, ethanol production using corn stover in the study region would have strong positive ripple effects, with the values of multipliers varying with greenhouse gas price and national energy security premium. The relatively high multiplier values suggest that a large portion of the value associated with corn stover ethanol production would accrue to the downstream end of the value chain instead of stover producers.

Agent-Based Modeling in Public Health: Current Applications and Future Directions.

PubMed

Tracy, Melissa; Cerdá, Magdalena; Keyes, Katherine M

2018-04-01

Agent-based modeling is a computational approach in which agents with a specified set of characteristics interact with each other and with their environment according to predefined rules. We review key areas in public health where agent-based modeling has been adopted, including both communicable and noncommunicable disease, health behaviors, and social epidemiology. We also describe the main strengths and limitations of this approach for questions with public health relevance. Finally, we describe both methodologic and substantive future directions that we believe will enhance the value of agent-based modeling for public health. In particular, advances in model validation, comparisons with other causal modeling procedures, and the expansion of the models to consider comorbidity and joint influences more systematically will improve the utility of this approach to inform public health research, practice, and policy.

Integrating macro and micro scale approaches in the agent-based modeling of residential dynamics

NASA Astrophysics Data System (ADS)

Saeedi, Sara

2018-06-01

With the advancement of computational modeling and simulation (M&S) methods as well as data collection technologies, urban dynamics modeling substantially improved over the last several decades. The complex urban dynamics processes are most effectively modeled not at the macro-scale, but following a bottom-up approach, by simulating the decisions of individual entities, or residents. Agent-based modeling (ABM) provides the key to a dynamic M&S framework that is able to integrate socioeconomic with environmental models, and to operate at both micro and macro geographical scales. In this study, a multi-agent system is proposed to simulate residential dynamics by considering spatiotemporal land use changes. In the proposed ABM, macro-scale land use change prediction is modeled by Artificial Neural Network (ANN) and deployed as the agent environment and micro-scale residential dynamics behaviors autonomously implemented by household agents. These two levels of simulation interacted and jointly promoted urbanization process in an urban area of Tehran city in Iran. The model simulates the behavior of individual households in finding ideal locations to dwell. The household agents are divided into three main groups based on their income rank and they are further classified into different categories based on a number of attributes. These attributes determine the households' preferences for finding new dwellings and change with time. The ABM environment is represented by a land-use map in which the properties of the land parcels change dynamically over the simulation time. The outputs of this model are a set of maps showing the pattern of different groups of households in the city. These patterns can be used by city planners to find optimum locations for building new residential units or adding new services to the city. The simulation results show that combining macro- and micro-level simulation can give full play to the potential of the ABM to understand the driving

Computer-Aided Structure Based Drug Design Approaches for the Discovery of New Anti-CHIKV Agents.

PubMed

Jadav, Surender Singh; Sinha, Barij Nayan; Hilgenfeld, Rolf; Jayaprakash, Venkatesan

2017-11-10

Chikungunya is a viral infection caused by Chikungunya virus (CHIKV), an arbovirus transmitted through mosquito (Aedes aegypti and Aedes albopictus) bite. The virus from sylvatic cycle in Africa mutated to new vector adaptation and became one of the major emerging and re-emerging viral infections in the past decade, affecting more than 40 countries. Efforts are being made by many researches to develop means to prevent and control the infection through vaccines and vector control strategy. On the other hand, search for novel chemotherapeutic agents for the treatment of infected patients is on. Approach of repurposed drug is one way of identifying an existing drug for the treatment of CHIKV infection. Review the history of CHIKV nsp2 protease inhibitors derived through structure-based computer-aided drug design along with phytochemicals identified as anti-CHIKV agents. A survey on CHIKV inhibitors reported till date has been carriedout. The data obtained were organized and discussed under natural substances and synthetic derivatives obtained as result of rational design. The review provides a well organized content in chronological order that has highly significant information for medicinal chemist who wish to explore the area of Anti-CHIKV drug design and development. Natural compounds with different scaffolds provides an opportunity to explore Ligand based drug design (LBDD), while rational drug design approaches provides opportunity to explore the Structure based drug design. From the presented mini-review, readers can understand that this area is less explored and has lots of potential in anti-CHIKVviral drug design & development. of reported literature inferred that, unlike other viral proteases, the nsP2 protease can be targeted for CHIKV viral inhibition. The HTVS process for the identification of anti-CHIK agents provided a few successive validated lead compounds against CHIKV infections. Copyright© Bentham Science Publishers; For any queries, please email

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.

Using Informatics-, Bioinformatics- and Genomics-Based Approaches for the Molecular Surveillance and Detection of Biothreat Agents

NASA Astrophysics Data System (ADS)

Seto, Donald

The convergence and wealth of informatics, bioinformatics and genomics methods and associated resources allow a comprehensive and rapid approach for the surveillance and detection of bacterial and viral organisms. Coupled with the continuing race for the fastest, most cost-efficient and highest-quality DNA sequencing technology, that is, "next generation sequencing", the detection of biological threat agents by `cheaper and faster' means is possible. With the application of improved bioinformatic tools for the understanding of these genomes and for parsing unique pathogen genome signatures, along with `state-of-the-art' informatics which include faster computational methods, equipment and databases, it is feasible to apply new algorithms to biothreat agent detection. Two such methods are high-throughput DNA sequencing-based and resequencing microarray-based identification. These are illustrated and validated by two examples involving human adenoviruses, both from real-world test beds.

Elements of decisional dynamics: An agent-based approach applied to artificial financial market

NASA Astrophysics Data System (ADS)

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2018-02-01

This paper introduces an original mathematical description for describing agents' decision-making process in the case of problems affected by both individual and collective behaviors in systems characterized by nonlinear, path dependent, and self-organizing interactions. An application to artificial financial markets is proposed by designing a multi-agent system based on the proposed formalization. In this application, agents' decision-making process is based on fuzzy logic rules and the price dynamics is purely deterministic according to the basic matching rules of a central order book. Finally, while putting most parameters under evolutionary control, the computational agent-based system is able to replicate several stylized facts of financial time series (distributions of stock returns showing a heavy tail with positive excess kurtosis, absence of autocorrelations in stock returns, and volatility clustering phenomenon).

Elements of decisional dynamics: An agent-based approach applied to artificial financial market.

PubMed

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2018-02-01

This paper introduces an original mathematical description for describing agents' decision-making process in the case of problems affected by both individual and collective behaviors in systems characterized by nonlinear, path dependent, and self-organizing interactions. An application to artificial financial markets is proposed by designing a multi-agent system based on the proposed formalization. In this application, agents' decision-making process is based on fuzzy logic rules and the price dynamics is purely deterministic according to the basic matching rules of a central order book. Finally, while putting most parameters under evolutionary control, the computational agent-based system is able to replicate several stylized facts of financial time series (distributions of stock returns showing a heavy tail with positive excess kurtosis, absence of autocorrelations in stock returns, and volatility clustering phenomenon).

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.

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.

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

NASA Astrophysics Data System (ADS)

Cenek, Martin; Dahl, Spencer K.

2016-11-01

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

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

PubMed

Cenek, Martin; Dahl, Spencer K

2016-11-01

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

Combining Computational Fluid Dynamics and Agent-Based Modeling: A New Approach to Evacuation Planning

PubMed Central

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

2011-01-01

We introduce a novel hybrid of two fields—Computational Fluid Dynamics (CFD) and Agent-Based Modeling (ABM)—as a powerful new technique for urban evacuation planning. CFD is a predominant technique for modeling airborne transport of contaminants, while ABM is a powerful approach for modeling social dynamics in populations of adaptive individuals. The hybrid CFD-ABM method is capable of simulating how large, spatially-distributed populations might respond to a physically realistic contaminant plume. We demonstrate the overall feasibility of CFD-ABM evacuation design, using the case of a hypothetical aerosol release in Los Angeles to explore potential effectiveness of various policy regimes. We conclude by arguing that this new approach can be powerfully applied to arbitrary population centers, offering an unprecedented preparedness and catastrophic event response tool. PMID:21687788

An agent-oriented approach to automated mission operations

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Odubiyi, Jide

1994-01-01

As we plan for the next generation of Mission Operations Control Center (MOCC) systems, there are many opportunities for the increased utilization of innovative knowledge-based technologies. The innovative technology discussed is an advanced use of agent-oriented approaches to the automation of mission operations. The paper presents an overview of this technology and discusses applied operational scenarios currently being investigated and prototyped. A major focus of the current work is the development of a simple user mechanism that would empower operations staff members to create, in real time, software agents to assist them in common, labor intensive operations tasks. These operational tasks would include: handling routine data and information management functions; amplifying the capabilities of a spacecraft analyst/operator to rapidly identify, analyze, and correct spacecraft anomalies by correlating complex data/information sets and filtering error messages; improving routine monitoring and trend analysis by detecting common failure signatures; and serving as a sentinel for spacecraft changes during critical maneuvers enhancing the system's capabilities to support nonroutine operational conditions with minimum additional staff. An agent-based testbed is under development. This testbed will allow us to: (1) more clearly understand the intricacies of applying agent-based technology in support of the advanced automation of mission operations and (2) access the full set of benefits that can be realized by the proper application of agent-oriented technology in a mission operations environment. The testbed under development addresses some of the data management and report generation functions for the Explorer Platform (EP)/Extreme UltraViolet Explorer (EUVE) Flight Operations Team (FOT). We present an overview of agent-oriented technology and a detailed report on the operation's concept for the testbed.

Agent-based modeling approach of immune defense against spores of opportunistic human pathogenic fungi.

PubMed

Tokarski, Christian; Hummert, Sabine; Mech, Franziska; Figge, Marc Thilo; Germerodt, Sebastian; Schroeter, Anja; Schuster, Stefan

2012-01-01

Opportunistic human pathogenic fungi like the ubiquitous fungus Aspergillus fumigatus are a major threat to immunocompromised patients. An impaired immune system renders the body vulnerable to invasive mycoses that often lead to the death of the patient. While the number of immunocompromised patients is rising with medical progress, the process, and dynamics of defense against invaded and ready to germinate fungal conidia are still insufficiently understood. Besides macrophages, neutrophil granulocytes form an important line of defense in that they clear conidia. Live imaging shows the interaction of those phagocytes and conidia as a dynamic process of touching, dragging, and phagocytosis. To unravel strategies of phagocytes on the hunt for conidia an agent-based modeling approach is used, implemented in NetLogo. Different modes of movement of phagocytes are tested regarding their clearing efficiency: random walk, short-term persistence in their recent direction, chemotaxis of chemokines excreted by conidia, and communication between phagocytes. While the short-term persistence hunting strategy turned out to be superior to the simple random walk, following a gradient of chemokines released by conidial agents is even better. The advantage of communication between neutrophilic agents showed a strong dependency on the spatial scale of the focused area and the distribution of the pathogens.

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

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.

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.

B-tree search reinforcement learning for model based intelligent agent

NASA Astrophysics Data System (ADS)

Bhuvaneswari, S.; Vignashwaran, R.

2013-03-01

Agents trained by learning techniques provide a powerful approximation of active solutions for naive approaches. In this study using B - Trees implying reinforced learning the data search for information retrieval is moderated to achieve accuracy with minimum search time. The impact of variables and tactics applied in training are determined using reinforcement learning. Agents based on these techniques perform satisfactory baseline and act as finite agents based on the predetermined model against competitors from the course.

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. Copyright © 2014 Elsevier Ltd. All rights reserved.

Simulating Cancer Growth with Multiscale Agent-Based Modeling

PubMed Central

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

2014-01-01

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. PMID:24793698

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.

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

PubMed

Lawlor, Jennifer A; McGirr, Sara

2017-12-01

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

Agent-based approach for generation of a money-centered star network

NASA Astrophysics Data System (ADS)

Yang, Jae-Suk; Kwon, Okyu; Jung, Woo-Sung; Kim, In-mook

2008-09-01

The history of trade is a progression from a pure barter system. A medium of exchange emerges autonomously in the market, a position currently occupied by money. We investigate an agent-based computational economics model consisting of interacting agents considering distinguishable properties of commodities which represent salability. We also analyze the properties of the commodity network using a spanning tree. We find that the “storage fee” is more crucial than “demand” in determining which commodity is used as a medium of exchange.

A systems approach to healthcare: agent-based modeling, community mental health, and population well-being.

PubMed

Silverman, Barry G; Hanrahan, Nancy; Bharathy, Gnana; Gordon, Kim; Johnson, Dan

2015-02-01

Explore whether agent-based modeling and simulation can help healthcare administrators discover interventions that increase population wellness and quality of care while, simultaneously, decreasing costs. Since important dynamics often lie in the social determinants outside the health facilities that provide services, this study thus models the problem at three levels (individuals, organizations, and society). The study explores the utility of translating an existing (prize winning) software for modeling complex societal systems and agent's daily life activities (like a Sim City style of software), into a desired decision support system. A case study tests if the 3 levels of system modeling approach is feasible, valid, and useful. The case study involves an urban population with serious mental health and Philadelphia's Medicaid population (n=527,056), in particular. Section 3 explains the models using data from the case study and thereby establishes feasibility of the approach for modeling a real system. The models were trained and tuned using national epidemiologic datasets and various domain expert inputs. To avoid co-mingling of training and testing data, the simulations were then run and compared (Section 4.1) to an analysis of 250,000 Philadelphia patient hospital admissions for the year 2010 in terms of re-hospitalization rate, number of doctor visits, and days in hospital. Based on the Student t-test, deviations between simulated vs. real world outcomes are not statistically significant. Validity is thus established for the 2008-2010 timeframe. We computed models of various types of interventions that were ineffective as well as 4 categories of interventions (e.g., reduced per-nurse caseload, increased check-ins and stays, etc.) that result in improvement in well-being and cost. The 3 level approach appears to be useful to help health administrators sort through system complexities to find effective interventions at lower costs. Copyright © 2014 Elsevier B

Intercell scheduling: A negotiation approach using multi-agent coalitions

NASA Astrophysics Data System (ADS)

Tian, Yunna; Li, Dongni; Zheng, Dan; Jia, Yunde

2016-10-01

Intercell scheduling problems arise as a result of intercell transfers in cellular manufacturing systems. Flexible intercell routes are considered in this article, and a coalition-based scheduling (CBS) approach using distributed multi-agent negotiation is developed. Taking advantage of the extended vision of the coalition agents, the global optimization is improved and the communication cost is reduced. The objective of the addressed problem is to minimize mean tardiness. Computational results show that, compared with the widely used combinatorial rules, CBS provides better performance not only in minimizing the objective, i.e. mean tardiness, but also in minimizing auxiliary measures such as maximum completion time, mean flow time and the ratio of tardy parts. Moreover, CBS is better than the existing intercell scheduling approach for the same problem with respect to the solution quality and computational costs.

Modeling of a production system using the multi-agent approach

NASA Astrophysics Data System (ADS)

Gwiazda, A.; Sękala, A.; Banaś, W.

2017-08-01

The method that allows for the analysis of complex systems is a multi-agent simulation. The multi-agent simulation (Agent-based modeling and simulation - ABMS) is modeling of complex systems consisting of independent agents. In the case of the model of the production system agents may be manufactured pieces set apart from other types of agents like machine tools, conveyors or replacements stands. Agents are magazines and buffers. More generally speaking, the agents in the model can be single individuals, but you can also be defined as agents of collective entities. They are allowed hierarchical structures. It means that a single agent could belong to a certain class. Depending on the needs of the agent may also be a natural or physical resource. From a technical point of view, the agent is a bundle of data and rules describing its behavior in different situations. Agents can be autonomous or non-autonomous in making the decision about the types of classes of agents, class sizes and types of connections between elements of the system. Multi-agent modeling is a very flexible technique for modeling and model creating in the convention that could be adapted to any research problem analyzed from different points of views. One of the major problems associated with the organization of production is the spatial organization of the production process. Secondly, it is important to include the optimal scheduling. For this purpose use can approach multi-purposeful. In this regard, the model of the production process will refer to the design and scheduling of production space for four different elements. The program system was developed in the environment NetLogo. It was also used elements of artificial intelligence. The main agent represents the manufactured pieces that, according to previously assumed rules, generate the technological route and allow preprint the schedule of that line. Machine lines, reorientation stands, conveyors and transport devices also represent the

Contract Monitoring in Agent-Based Systems: Case Study

NASA Astrophysics Data System (ADS)

Hodík, Jiří; Vokřínek, Jiří; Jakob, Michal

Monitoring of fulfilment of obligations defined by electronic contracts in distributed domains is presented in this paper. A two-level model of contract-based systems and the types of observations needed for contract monitoring are introduced. The observations (inter-agent communication and agents’ actions) are collected and processed by the contract observation and analysis pipeline. The presented approach has been utilized in a multi-agent system for electronic contracting in a modular certification testing domain.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

North, M. J.; Howe, T. R.; Collier, N. T.

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 ormore » 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.« less

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

Numeric, Agent-based or System Dynamics Model? Which Modeling Approach is the Best for Vast Population Simulation?

PubMed

Cimler, Richard; Tomaskova, Hana; Kuhnova, Jitka; Dolezal, Ondrej; Pscheidl, Pavel; Kuca, Kamil

2018-01-01

Alzheimer's disease is one of the most common mental illnesses. It is posited that more than 25% of the population is affected by some mental disease during their lifetime. Treatment of each patient draws resources from the economy concerned. Therefore, it is important to quantify the potential economic impact. Agent-based, system dynamics and numerical approaches to dynamic modeling of the population of the European Union and its patients with Alzheimer's disease are presented in this article. Simulations, their characteristics, and the results from different modeling tools are compared. The results of these approaches are compared with EU population growth predictions from the statistical office of the EU by Eurostat. The methodology of a creation of the models is described and all three modeling approaches are compared. The suitability of each modeling approach for the population modeling is discussed. In this case study, all three approaches gave us the results corresponding with the EU population prediction. Moreover, we were able to predict the number of patients with AD and, based on the modeling method, we were also able to monitor different characteristics of the population. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Agents, Bayes, and Climatic Risks - a modular modelling approach

NASA Astrophysics Data System (ADS)

Haas, A.; Jaeger, C.

2005-08-01

When insurance firms, energy companies, governments, NGOs, and other agents strive to manage climatic risks, it is by no way clear what the aggregate outcome should and will be. As a framework for investigating this subject, we present the LAGOM model family. It is based on modules depicting learning social agents. For managing climate risks, our agents use second order probabilities and update them by means of a Bayesian mechanism while differing in priors and risk aversion. The interactions between these modules and the aggregate outcomes of their actions are implemented using further modules. The software system is implemented as a series of parallel processes using the CIAMn approach. It is possible to couple modules irrespective of the language they are written in, the operating system under which they are run, and the physical location of the machine.

Discovery of novel anti-HIV agents via Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC) click chemistry-based approach.

PubMed

Gao, Ping; Sun, Lin; Zhou, Junsu; Li, Xiao; Zhan, Peng; Liu, Xinyong

2016-09-01

In recent years, a variety of new synthetic methodologies and concepts have been proposed in the search for new pharmaceutical lead structures and optimization. Notably, the Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC) click chemistry approach has drawn great attention and has become a powerful tool for the generation of privileged medicinal skeletons in the discovery of anti-HIV agents. This is due to the high degree of reliability, complete specificity (chemoselectivity and regioselectivity), mild conditions, and the biocompatibility of the reactants. Herein, the authors describe the progress thus far on the discovery of novel anti-HIV agents via the CuAAC click chemistry-based approach. CuAAC click chemistry is a proven protocol for synthesizing triazole products which could serve as basic pharmacophores, act as replacements of traditional scaffold or substituent modification, be a linker of dual-target or dual-site inhibitors and more for the discovery of novel anti-HIV agents. What's more, it also provides convenience and feasibility for dynamic combinatorial chemistry and in situ screening. It is envisioned that click chemistry will draw more attention and make more contributions in anti-HIV drug discovery in the future.

A Multi Agent Based Approach for Prehospital Emergency Management.

PubMed

Safdari, Reza; Shoshtarian Malak, Jaleh; Mohammadzadeh, Niloofar; Danesh Shahraki, Azimeh

2017-07-01

To demonstrate an architecture to automate the prehospital emergency process to categorize the specialized care according to the situation at the right time for reducing the patient mortality and morbidity. Prehospital emergency process were analyzed using existing prehospital management systems, frameworks and the extracted process were modeled using sequence diagram in Rational Rose software. System main agents were identified and modeled via component diagram, considering the main system actors and by logically dividing business functionalities, finally the conceptual architecture for prehospital emergency management was proposed. The proposed architecture was simulated using Anylogic simulation software. Anylogic Agent Model, State Chart and Process Model were used to model the system. Multi agent systems (MAS) had a great success in distributed, complex and dynamic problem solving environments, and utilizing autonomous agents provides intelligent decision making capabilities.  The proposed architecture presents prehospital management operations. The main identified agents are: EMS Center, Ambulance, Traffic Station, Healthcare Provider, Patient, Consultation Center, National Medical Record System and quality of service monitoring agent. In a critical condition like prehospital emergency we are coping with sophisticated processes like ambulance navigation health care provider and service assignment, consultation, recalling patients past medical history through a centralized EHR system and monitoring healthcare quality in a real-time manner. The main advantage of our work has been the multi agent system utilization. Our Future work will include proposed architecture implementation and evaluation of its impact on patient quality care improvement.

A Multi Agent Based Approach for Prehospital Emergency Management

PubMed Central

Safdari, Reza; Shoshtarian Malak, Jaleh; Mohammadzadeh, Niloofar; Danesh Shahraki, Azimeh

2017-01-01

Objective: To demonstrate an architecture to automate the prehospital emergency process to categorize the specialized care according to the situation at the right time for reducing the patient mortality and morbidity. Methods: Prehospital emergency process were analyzed using existing prehospital management systems, frameworks and the extracted process were modeled using sequence diagram in Rational Rose software. System main agents were identified and modeled via component diagram, considering the main system actors and by logically dividing business functionalities, finally the conceptual architecture for prehospital emergency management was proposed. The proposed architecture was simulated using Anylogic simulation software. Anylogic Agent Model, State Chart and Process Model were used to model the system. Results: Multi agent systems (MAS) had a great success in distributed, complex and dynamic problem solving environments, and utilizing autonomous agents provides intelligent decision making capabilities.  The proposed architecture presents prehospital management operations. The main identified agents are: EMS Center, Ambulance, Traffic Station, Healthcare Provider, Patient, Consultation Center, National Medical Record System and quality of service monitoring agent. Conclusion: In a critical condition like prehospital emergency we are coping with sophisticated processes like ambulance navigation health care provider and service assignment, consultation, recalling patients past medical history through a centralized EHR system and monitoring healthcare quality in a real-time manner. The main advantage of our work has been the multi agent system utilization. Our Future work will include proposed architecture implementation and evaluation of its impact on patient quality care improvement. PMID:28795061

A review of agent-based modeling approach in the supply chain collaboration context

NASA Astrophysics Data System (ADS)

Arvitrida, N. I.

2018-04-01

Collaboration is considered as the key aspect of supply chain management (SCM) success. This issue has been addressed by many studies in recent years, but there are still few research employs agent-based modeling (ABM) approach to study business partnerships in SCM. This paper reviews the use of ABM in modeling collaboration in supply chains and inform the scope of ABM application in the existing literature. The review reveals that ABM can be an effective tool to address various aspects in supply chain relationships, but its applications in SCM studies are still limited. Moreover, where ABM is applied in the SCM context, most of the studies focus on software architecture rather than analyzing the supply chain issues. This paper also provides insights to SCM researchers about the opportunity uses of ABM in studying complexity in supply chain collaboration.

Risk, individual differences, and environment: an Agent-Based Modeling approach to sexual risk-taking.

PubMed

Nagoski, Emily; Janssen, Erick; Lohrmann, David; Nichols, Eric

2012-08-01

Risky sexual behaviors, including the decision to have unprotected sex, result from interactions between individuals and their environment. The current study explored the use of Agent-Based Modeling (ABM)-a methodological approach in which computer-generated artificial societies simulate human sexual networks-to assess the influence of heterogeneity of sexual motivation on the risk of contracting HIV. The models successfully simulated some characteristics of human sexual systems, such as the relationship between individual differences in sexual motivation (sexual excitation and inhibition) and sexual risk, but failed to reproduce the scale-free distribution of number of partners observed in the real world. ABM has the potential to inform intervention strategies that target the interaction between an individual and his or her social environment.

A Multi-Agent Approach to the Simulation of Robotized Manufacturing Systems

NASA Astrophysics Data System (ADS)

Foit, K.; Gwiazda, A.; Banaś, W.

2016-08-01

The recent years of eventful industry development, brought many competing products, addressed to the same market segment. The shortening of a development cycle became a necessity if the company would like to be competitive. Because of switching to the Intelligent Manufacturing model the industry search for new scheduling algorithms, while the traditional ones do not meet the current requirements. The agent-based approach has been considered by many researchers as an important way of evolution of modern manufacturing systems. Due to the properties of the multi-agent systems, this methodology is very helpful during creation of the model of production system, allowing depicting both processing and informational part. The complexity of such approach makes the analysis impossible without the computer assistance. Computer simulation still uses a mathematical model to recreate a real situation, but nowadays the 2D or 3D virtual environments or even virtual reality have been used for realistic illustration of the considered systems. This paper will focus on robotized manufacturing system and will present the one of possible approaches to the simulation of such systems. The selection of multi-agent approach is motivated by the flexibility of this solution that offers the modularity, robustness and autonomy.

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.

A New Multi-Agent Approach to Adaptive E-Education

NASA Astrophysics Data System (ADS)

Chen, Jing; Cheng, Peng

Improving customer satisfaction degree is important in e-Education. This paper describes a new approach to adaptive e-Education taking into account the full spectrum of Web service techniques and activities. It presents a multi-agents architecture based on artificial psychology techniques, which makes the e-Education process both adaptable and dynamic, and hence up-to-date. Knowledge base techniques are used to support the e-Education process, and artificial psychology techniques to deal with user psychology, which makes the e-Education system more effective and satisfying.

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

PubMed Central

Marshall, Brandon D. L.; Galea, Sandro

2015-01-01

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

Design and Simulation of Material-Integrated Distributed Sensor Processing with a Code-Based Agent Platform and Mobile Multi-Agent Systems

PubMed Central

Bosse, Stefan

2015-01-01

Multi-agent systems (MAS) can be used for decentralized and self-organizing data processing in a distributed system, like a resource-constrained sensor network, enabling distributed information extraction, for example, based on pattern recognition and self-organization, by decomposing complex tasks in simpler cooperative agents. Reliable MAS-based data processing approaches can aid the material-integration of structural-monitoring applications, with agent processing platforms scaled to the microchip level. The agent behavior, based on a dynamic activity-transition graph (ATG) model, is implemented with program code storing the control and the data state of an agent, which is novel. The program code can be modified by the agent itself using code morphing techniques and is capable of migrating in the network between nodes. The program code is a self-contained unit (a container) and embeds the agent data, the initialization instructions and the ATG behavior implementation. The microchip agent processing platform used for the execution of the agent code is a standalone multi-core stack machine with a zero-operand instruction format, leading to a small-sized agent program code, low system complexity and high system performance. The agent processing is token-queue-based, similar to Petri-nets. The agent platform can be implemented in software, too, offering compatibility at the operational and code level, supporting agent processing in strong heterogeneous networks. In this work, the agent platform embedded in a large-scale distributed sensor network is simulated at the architectural level by using agent-based simulation techniques. PMID:25690550

Design and simulation of material-integrated distributed sensor processing with a code-based agent platform and mobile multi-agent systems.

PubMed

Bosse, Stefan

2015-02-16

Multi-agent systems (MAS) can be used for decentralized and self-organizing data processing in a distributed system, like a resource-constrained sensor network, enabling distributed information extraction, for example, based on pattern recognition and self-organization, by decomposing complex tasks in simpler cooperative agents. Reliable MAS-based data processing approaches can aid the material-integration of structural-monitoring applications, with agent processing platforms scaled to the microchip level. The agent behavior, based on a dynamic activity-transition graph (ATG) model, is implemented with program code storing the control and the data state of an agent, which is novel. The program code can be modified by the agent itself using code morphing techniques and is capable of migrating in the network between nodes. The program code is a self-contained unit (a container) and embeds the agent data, the initialization instructions and the ATG behavior implementation. The microchip agent processing platform used for the execution of the agent code is a standalone multi-core stack machine with a zero-operand instruction format, leading to a small-sized agent program code, low system complexity and high system performance. The agent processing is token-queue-based, similar to Petri-nets. The agent platform can be implemented in software, too, offering compatibility at the operational and code level, supporting agent processing in strong heterogeneous networks. In this work, the agent platform embedded in a large-scale distributed sensor network is simulated at the architectural level by using agent-based simulation techniques.

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.

A decentralised multi-agent approach to enhance the stability of smart microgrids with renewable energy

NASA Astrophysics Data System (ADS)

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

2016-05-01

This paper presents the impact of large penetration of wind power on the transient stability through a dynamic evaluation of the critical clearing times (CCTs) by using intelligent agent-based approach. A decentralised multi-agent-based framework is developed, where agents represent a number of physical device models to form a complex infrastructure for computation and communication. They enable the dynamic flow of information and energy for the interaction between the physical processes and their activities. These agents dynamically adapt online measurements and use the CCT information for relay coordination to improve the transient stability of power systems. Simulations are carried out on a smart microgrid system for faults at increasing wind power penetration levels and the improvement in transient stability using the proposed agent-based framework is demonstrated.

Nanostructured thermites based on iodine pentoxide for bio agent defeat systems.

NASA Astrophysics Data System (ADS)

Hobosyan, Mkhitar; Kazansky, Alexander; Martirosyan, Karen

2011-10-01

The risk for bioterrorist events involving the intentional airborne release of contagious agents has led to development of new approaches for bio agent defeat technologies both indoors and outdoors. Novel approaches to defeat harmful biological agents have generated a strong demand for new active materials. The preferred solutions are to neutralize the biological agents within the immediate target area by using aerosolized biocidal substances released in situ by high energetic reactions. By using nano-thermite reactions, with energy release up to 25 kJ/cc, based on I2O5/Al nanoparticles we intend to generate high quantity of vaporized iodine for spatial deposition onto harmful bacteria for their destruction. In this report, the effect of reaction product on growth and survival of Escherichia coli (E-coli) expressing GFP (Green Fluorescent Protein) was investigated. Moreover, we developed an approach to increase sensitivity of the detection. The study has shown that I2O5/Al nanosystem is extremely effective to disinfect harmful biological agents such (E-coli) bacteria in seconds.

Dynamical systems approach to the study of a sociophysics agent-based model

NASA Astrophysics Data System (ADS)

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

2011-03-01

The Sznajd model is a Potts-like model that has been studied in the context of sociophysics [1,2] (where spins are interpreted as opinions). In a recent work [3], we generalized the Sznajd model to include assymetric interactions between the spins (interpreted as biases towards opinions) and used dynamical systems techniques to tackle its mean-field version, given by the flow: ησ = ∑ σ' = 1Mησησ'(ησρσ'→σ-σ'ρσ→σ'). Where hs is the proportion of agents with opinion (spin) σ', M is the number of opinions and σ'→σ' is the probability weight for an agent with opinion σ being convinced by another agent with opinion σ'. We made Monte Carlo simulations of the model in a complex network (using Barabási-Albert networks [4]) and they displayed the same attractors than the mean-field. Using linear stability analysis, we were able to determine the mean-field attractor structure analytically and to show that it has connections with well known graph theory problems (maximal independent sets and positive fluxes in directed graphs). Our dynamical systems approach is quite simple and can be used also in other models, like the voter model.

Agent autonomy approach to probabilistic physics-of-failure modeling of complex dynamic systems with interacting failure mechanisms

NASA Astrophysics Data System (ADS)

Gromek, Katherine Emily

A novel computational and inference framework of the physics-of-failure (PoF) reliability modeling for complex dynamic systems has been established in this research. The PoF-based reliability models are used to perform a real time simulation of system failure processes, so that the system level reliability modeling would constitute inferences from checking the status of component level reliability at any given time. The "agent autonomy" concept is applied as a solution method for the system-level probabilistic PoF-based (i.e. PPoF-based) modeling. This concept originated from artificial intelligence (AI) as a leading intelligent computational inference in modeling of multi agents systems (MAS). The concept of agent autonomy in the context of reliability modeling was first proposed by M. Azarkhail [1], where a fundamentally new idea of system representation by autonomous intelligent agents for the purpose of reliability modeling was introduced. Contribution of the current work lies in the further development of the agent anatomy concept, particularly the refined agent classification within the scope of the PoF-based system reliability modeling, new approaches to the learning and the autonomy properties of the intelligent agents, and modeling interacting failure mechanisms within the dynamic engineering system. The autonomous property of intelligent agents is defined as agent's ability to self-activate, deactivate or completely redefine their role in the analysis. This property of agents and the ability to model interacting failure mechanisms of the system elements makes the agent autonomy fundamentally different from all existing methods of probabilistic PoF-based reliability modeling. 1. Azarkhail, M., "Agent Autonomy Approach to Physics-Based Reliability Modeling of Structures and Mechanical Systems", PhD thesis, University of Maryland, College Park, 2007.

The role of educational trainings in the diffusion of smart metering platforms: An agent-based modeling approach

NASA Astrophysics Data System (ADS)

Weron, Tomasz; Kowalska-Pyzalska, Anna; Weron, Rafał

2018-09-01

Using an agent-based modeling approach we examine the impact of educational programs and trainings on the diffusion of smart metering platforms (SMPs). We also investigate how social responses, like conformity or independence, mass-media advertising as well as opinion stability impact the transition from predecisional and preactional behavioral stages (opinion formation) to actional and postactional stages (decision-making) of individual electricity consumers. We find that mass-media advertising (i.e., a global external field) and educational trainings (i.e., a local external field) lead to similar, though not identical adoption rates. Secondly, that spatially concentrated 'group' trainings are never worse than randomly scattered ones, and for a certain range of parameters are significantly better. Finally, that by manipulating the time required by an agent to make a decision, e.g., through promotions, we can speed up or slow down the diffusion of SMPs.

Agent-based modelling in synthetic biology.

PubMed

Gorochowski, Thomas E

2016-11-30

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

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. © 2015 Society for Risk Analysis.

Cooperation based dynamic team formation in multi-agent auctions

NASA Astrophysics Data System (ADS)

Pippin, Charles E.; Christensen, Henrik

2012-06-01

Auction based methods are often used to perform distributed task allocation on multi-agent teams. Many existing approaches to auctions assume fully cooperative team members. On in-situ and dynamically formed teams, reciprocal collaboration may not always be a valid assumption. This paper presents an approach for dynamically selecting auction partners based on observed team member performance and shared reputation. In addition, we present the use of a shared reputation authority mechanism. Finally, experiments are performed in simulation on multiple UAV platforms to highlight situations in which it is better to enforce cooperation in auctions using this approach.

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).

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).

Model-Drive Architecture for Agent-Based Systems

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

A desirability-based multi objective approach for the virtual screening discovery of broad-spectrum anti-gastric cancer agents

PubMed Central

Sánchez-Rodríguez, Aminael; Tejera, Eduardo; Cruz-Monteagudo, Maykel; Borges, Fernanda; Cordeiro, M. Natália D. S.; Le-Thi-Thu, Huong; Pham-The, Hai

2018-01-01

Gastric cancer is the third leading cause of cancer-related mortality worldwide and despite advances in prevention, diagnosis and therapy, it is still regarded as a global health concern. The efficacy of the therapies for gastric cancer is limited by a poor response to currently available therapeutic regimens. One of the reasons that may explain these poor clinical outcomes is the highly heterogeneous nature of this disease. In this sense, it is essential to discover new molecular agents capable of targeting various gastric cancer subtypes simultaneously. Here, we present a multi-objective approach for the ligand-based virtual screening discovery of chemical compounds simultaneously active against the gastric cancer cell lines AGS, NCI-N87 and SNU-1. The proposed approach relays in a novel methodology based on the development of ensemble models for the bioactivity prediction against each individual gastric cancer cell line. The methodology includes the aggregation of one ensemble per cell line using a desirability-based algorithm into virtual screening protocols. Our research leads to the proposal of a multi-targeted virtual screening protocol able to achieve high enrichment of known chemicals with anti-gastric cancer activity. Specifically, our results indicate that, using the proposed protocol, it is possible to retrieve almost 20 more times multi-targeted compounds in the first 1% of the ranked list than what is expected from a uniform distribution of the active ones in the virtual screening database. More importantly, the proposed protocol attains an outstanding initial enrichment of known multi-targeted anti-gastric cancer agents. PMID:29420638

A Coupled Simulation Architecture for Agent-Based/Geohydrological Modelling

NASA Astrophysics Data System (ADS)

Jaxa-Rozen, M.

2016-12-01

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

A Distributed Ambient Intelligence Based Multi-Agent System for Alzheimer Health Care

NASA Astrophysics Data System (ADS)

Tapia, Dante I.; RodríGuez, Sara; Corchado, Juan M.

This chapter presents ALZ-MAS (Alzheimer multi-agent system), an ambient intelligence (AmI)-based multi-agent system aimed at enhancing the assistance and health care for Alzheimer patients. The system makes use of several context-aware technologies that allow it to automatically obtain information from users and the environment in an evenly distributed way, focusing on the characteristics of ubiquity, awareness, intelligence, mobility, etc., all of which are concepts defined by AmI. ALZ-MAS makes use of a services oriented multi-agent architecture, called flexible user and services oriented multi-agent architecture, to distribute resources and enhance its performance. It is demonstrated that a SOA approach is adequate to build distributed and highly dynamic AmI-based multi-agent systems.

Stability of subsystem solutions in agent-based models

NASA Astrophysics Data System (ADS)

Perc, Matjaž

2018-01-01

The fact that relatively simple entities, such as particles or neurons, or even ants or bees or humans, give rise to fascinatingly complex behaviour when interacting in large numbers is the hallmark of complex systems science. Agent-based models are frequently employed for modelling and obtaining a predictive understanding of complex systems. Since the sheer number of equations that describe the behaviour of an entire agent-based model often makes it impossible to solve such models exactly, Monte Carlo simulation methods must be used for the analysis. However, unlike pairwise interactions among particles that typically govern solid-state physics systems, interactions among agents that describe systems in biology, sociology or the humanities often involve group interactions, and they also involve a larger number of possible states even for the most simplified description of reality. This begets the question: when can we be certain that an observed simulation outcome of an agent-based model is actually stable and valid in the large system-size limit? The latter is key for the correct determination of phase transitions between different stable solutions, and for the understanding of the underlying microscopic processes that led to these phase transitions. We show that a satisfactory answer can only be obtained by means of a complete stability analysis of subsystem solutions. A subsystem solution can be formed by any subset of all possible agent states. The winner between two subsystem solutions can be determined by the average moving direction of the invasion front that separates them, yet it is crucial that the competing subsystem solutions are characterised by a proper composition and spatiotemporal structure before the competition starts. We use the spatial public goods game with diverse tolerance as an example, but the approach has relevance for a wide variety of agent-based models.

Story-Based Pedagogical Agents: A Scaffolding Design Approach for the Process of Historical Inquiry in a Web-Based Self-Learning Environment

ERIC Educational Resources Information Center

Fujimoto, Toru

2010-01-01

The purpose of this research was to design and evaluate a web-based self-learning environment for historical inquiry embedded with different types of instructional support featuring story-based pedagogical agents. This research focused on designing a learning environment by integrating story-based instruction and pedagogical agents as a means to…

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.

Evaluating Outdoor Water Use Demand under Changing Climatic and Demographic Conditions: An Agent-based Modeling Approach

NASA Astrophysics Data System (ADS)

Kanta, L.

2016-12-01

Outdoor water use for landscape and irrigation constitutes a significant end use in residential water demand. In periods of water shortages, utilities may reduce garden demands by implementing irrigation system audits, rebate programs, local ordinances, and voluntary or mandatory water use restrictions. Because utilities do not typically record outdoor and indoor water uses separately, the effects of policies for reducing garden demands cannot be readily calculated. The volume of water required to meet garden demands depends on the housing density or lawn size, type of vegetation, climatic conditions, efficiency of garden irrigation systems, and consumer water-use behaviors. Many existing outdoor demand estimation methods are deterministic and do not include consumer responses to conservation campaigns. In addition, mandatory restrictions may have a substantial impact on reducing outdoor demands, but the effectiveness of mandatory restrictions depends on the timing and the frequency of restrictions, in addition to the distribution of housing density and consumer types within a community. This research investigates a garden end-use model by coupling an agent-based modeling approach and a mechanistic-stochastic water demand model to create a methodology for estimating garden demand and evaluating demand reduction policies. The garden demand model is developed for two water utilities, using a diverse data sets, including residential customer billing records, records of outdoor conservation programs, frequency and type of mandatory water use restrictions, lot size distribution, population growth, and climatic data. A set of garden irrigation parameter values, which are based on the efficiency of irrigation systems and irrigation habits of consumers, are determined for a set of conservation ordinances and restrictions. The model parameters are then validated using customer water usage data from the participating water utilities. A sensitivity analysis is conducted for

Evaluating Outdoor Water Use Demand under Changing Climatic and Demographic Conditions: An Agent-based Modeling Approach

NASA Astrophysics Data System (ADS)

Kanta, L.; Berglund, E. Z.; Soh, M. H.

2017-12-01

Outdoor water-use for landscape and irrigation constitutes a significant end-use in total residential water demand. In periods of water shortages, utilities may reduce garden demands by implementing irrigation system audits, rebate programs, local ordinances, and voluntary or mandatory water-use restrictions. Because utilities do not typically record outdoor and indoor water-uses separately, the effects of policies for reducing garden demands cannot be readily calculated. The volume of water required to meet garden demands depends on the housing density, lawn size, type of vegetation, climatic conditions, efficiency of garden irrigation systems, and consumer water-use behaviors. Many existing outdoor demand estimation methods are deterministic and do not include consumer responses to conservation campaigns. In addition, mandatory restrictions may have a substantial impact on reducing outdoor demands, but the effectiveness of mandatory restrictions depends on the timing and the frequency of restrictions, in addition to the distribution of housing density and consumer types within a community. This research investigates a garden end-use model by coupling an agent-based modeling approach and a mechanistic-stochastic water demand model to create a methodology for estimating garden demand and evaluating demand reduction policies. The garden demand model is developed for two water utilities, using a diverse data sets, including residential customer billing records, outdoor conservation programs, frequency and type of mandatory water-use restrictions, lot size distribution, population growth, and climatic data. A set of garden irrigation parameter values, which are based on the efficiency of irrigation systems and irrigation habits of consumers, are determined for a set of conservation ordinances and restrictions. The model parameters are then validated using customer water usage data from the participating water utilities. A sensitivity analysis is conducted for garden

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. © The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Agent-Based Chemical Plume Tracing Using Fluid Dynamics

NASA Technical Reports Server (NTRS)

Zarzhitsky, Dimitri; Spears, Diana; Thayer, David; Spears, William

2004-01-01

This paper presents a rigorous evaluation of a novel, distributed chemical plume tracing algorithm. The algorithm is a combination of the best aspects of the two most popular predecessors for this task. Furthermore, it is based on solid, formal principles from the field of fluid mechanics. The algorithm is applied by a network of mobile sensing agents (e.g., robots or micro-air vehicles) that sense the ambient fluid velocity and chemical concentration, and calculate derivatives. The algorithm drives the robotic network to the source of the toxic plume, where measures can be taken to disable the source emitter. This work is part of a much larger effort in research and development of a physics-based approach to developing networks of mobile sensing agents for monitoring, tracking, reporting and responding to hazardous conditions.

A New Approach in the Preparation of Dendrimer-Based Bifunctional Diethylenetriaminepentaacetic Acid MR Contrast Agent Derivatives

PubMed Central

Nwe, Kido; Xu, Heng; Regino, Celeste Aida S.; Bernardo, Marcelino; Ileva, Lilia; Riffle, Lisa; Wong, Karen J.; Brechbiel, Martin W.

2009-01-01

In this paper we report a new method to prepare and characterize a contrast agent based on a fourth-generation (G4) polyamidoamine (PAMAM) dendrimer conjugated to the gadolinium complex of the bifunctional diethylenetriamine pentaacetic acid derivative (1B4M-DTPA). The method involves pre-forming the metal-ligand chelate in alcohol prior to conjugation to the dendrimer. The dendrimer-based agent was purified by a Sephadex® G-25 column and characterized by elemental analysis. The analysis and SEHPLC data gave a chelate to dendrimer ratio of 30:1 suggesting conjugation at approximately every other amine terminal on the dendrimer. Molar relaxivity of the agent measured at pH 7.4 displayed a higher value than that of the analogous G4 dendrimer based agent prepared by the post-metal incorporation method (r1 = 26.9 vs. 13.9 mM-1s-1 at 3T and 22°C). This is hypothesized to be due to the higher hydrophobicity of this conjugate, and the lack of available charged carboxylate groups from non-complexed free ligands that might coordinate to the metal and thus also reduce water exchange sites. Additionally, the distribution populations of compounds that result from the post-metal incorporation route are eliminated from the current product simplifying characterization as quality control issues pertaining to the production of such agents for clinical use as MR contrast agents. In vivo imaging in mice showed a reasonably fast clearance (t1/2 = 24 min) suggesting a viable agent for use in clinical application. PMID:19555072

A new approach in the preparation of dendrimer-based bifunctional diethylenetriaminepentaacetic acid MR contrast agent derivatives.

PubMed

Nwe, Kido; Xu, Heng; Regino, Celeste Aida S; Bernardo, Marcelino; Ileva, Lilia; Riffle, Lisa; Wong, Karen J; Brechbiel, Martin W

2009-07-01

In this paper, we report a new method to prepare and characterize a contrast agent based on a fourth-generation (G4) polyamidoamine (PAMAM) dendrimer conjugated to the gadolinium complex of the bifunctional diethylenetriamine pentaacetic acid derivative (1B4M-DTPA). The method involves preforming the metal-ligand chelate in alcohol prior to conjugation to the dendrimer. The dendrimer-based agent was purified by a Sephadex G-25 column and characterized by elemental analysis. The analysis and SE-HPLC data gave a chelate to dendrimer ratio of 30:1 suggesting conjugation at approximately every other amine terminal on the dendrimer. Molar relaxivity of the agent measured at pH 7.4 displayed a higher value than that of the analogous G4 dendrimer based agent prepared by the postmetal incorporation method (r(1) = 26.9 vs 13.9 mM(-1) s(-1) at 3 T and 22 degrees C). This is hypothesized to be due to the higher hydrophobicity of this conjugate and the lack of available charged carboxylate groups from noncomplexed free ligands that might coordinate to the metal and thus also reduce water exchange sites. Additionally, the distribution populations of compounds that result from the postmetal incorporation route are eliminated from the current product simplifying characterization as quality control issues pertaining to the production of such agents for clinical use as MR contrast agents. In vivo imaging in mice showed a reasonably fast clearance (t(1/2) = 24 min) suggesting a viable agent for use in clinical application.

CATS-based Agents That Err

NASA Technical Reports Server (NTRS)

Callantine, Todd J.

2002-01-01

This report describes preliminary research on intelligent agents that make errors. Such agents are crucial to the development of novel agent-based techniques for assessing system safety. The agents extend an agent architecture derived from the Crew Activity Tracking System that has been used as the basis for air traffic controller agents. The report first reviews several error taxonomies. Next, it presents an overview of the air traffic controller agents, then details several mechanisms for causing the agents to err in realistic ways. The report presents a performance assessment of the error-generating agents, and identifies directions for further research. The research was supported by the System-Wide Accident Prevention element of the FAA/NASA Aviation Safety Program.

Transaction based approach

NASA Astrophysics Data System (ADS)

Hunka, Frantisek; Matula, Jiri

2017-07-01

Transaction based approach is utilized in some methodologies in business process modeling. Essential parts of these transactions are human beings. The notion of agent or actor role is usually used for them. The paper on a particular example describes possibilities of Design Engineering Methodology for Organizations (DEMO) and Resource-Event-Agent (REA) methodology. Whereas the DEMO methodology can be regarded as a generic methodology having its foundation in the theory of Enterprise Ontology the REA methodology is regarded as the domain specific methodology and has its origin in accountancy systems. The results of these approaches is that the DEMO methodology captures everything that happens in the reality with a good empirical evidence whereas the REA methodology captures only changes connected with economic events. Economic events represent either change of the property rights to economic resource or consumption or production of economic resources. This results from the essence of economic events and their connection to economic resources.

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

Study on the E-commerce platform based on the agent

NASA Astrophysics Data System (ADS)

Fu, Ruixue; Qin, Lishuan; Gao, Yinmin

2011-10-01

To solve problem of dynamic integration in e-commerce, the Multi-Agent architecture of electronic commerce platform system based on Agent and Ontology has been introduced, which includes three major types of agent, Ontology and rule collection. In this architecture, service agent and rule are used to realize the business process reengineering, the reuse of software component, and agility of the electronic commerce platform. To illustrate the architecture, a simulation work has been done and the results imply that the architecture provides a very efficient method to design and implement the flexible, distributed, open and intelligent electronic commerce platform system to solve problem of dynamic integration in ecommerce. The objective of this paper is to illustrate the architecture of electronic commerce platform system, and the approach how Agent and Ontology support the electronic commerce platform system.

DAMS: A Model to Assess Domino Effects by Using Agent-Based Modeling and Simulation.

PubMed

Zhang, Laobing; Landucci, Gabriele; Reniers, Genserik; Khakzad, Nima; Zhou, Jianfeng

2017-12-19

Historical data analysis shows that escalation accidents, so-called domino effects, have an important role in disastrous accidents in the chemical and process industries. In this study, an agent-based modeling and simulation approach is proposed to study the propagation of domino effects in the chemical and process industries. Different from the analytical or Monte Carlo simulation approaches, which normally study the domino effect at probabilistic network levels, the agent-based modeling technique explains the domino effects from a bottom-up perspective. In this approach, the installations involved in a domino effect are modeled as agents whereas the interactions among the installations (e.g., by means of heat radiation) are modeled via the basic rules of the agents. Application of the developed model to several case studies demonstrates the ability of the model not only in modeling higher-level domino effects and synergistic effects but also in accounting for temporal dependencies. The model can readily be applied to large-scale complicated cases. © 2017 Society for Risk Analysis.

Agent Architectures for Compliance

NASA Astrophysics Data System (ADS)

Burgemeestre, Brigitte; Hulstijn, Joris; Tan, Yao-Hua

A Normative Multi-Agent System consists of autonomous agents who must comply with social norms. Different kinds of norms make different assumptions about the cognitive architecture of the agents. For example, a principle-based norm assumes that agents can reflect upon the consequences of their actions; a rule-based formulation only assumes that agents can avoid violations. In this paper we present several cognitive agent architectures for self-monitoring and compliance. We show how different assumptions about the cognitive architecture lead to different information needs when assessing compliance. The approach is validated with a case study of horizontal monitoring, an approach to corporate tax auditing recently introduced by the Dutch Customs and Tax Authority.

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.

A Market-Based Approach to Multi-factory Scheduling

NASA Astrophysics Data System (ADS)

Vytelingum, Perukrishnen; Rogers, Alex; MacBeth, Douglas K.; Dutta, Partha; Stranjak, Armin; Jennings, Nicholas R.

In this paper, we report on the design of a novel market-based approach for decentralised scheduling across multiple factories. Specifically, because of the limitations of scheduling in a centralised manner - which requires a center to have complete and perfect information for optimality and the truthful revelation of potentially commercially private preferences to that center - we advocate an informationally decentralised approach that is both agile and dynamic. In particular, this work adopts a market-based approach for decentralised scheduling by considering the different stakeholders representing different factories as self-interested, profit-motivated economic agents that trade resources for the scheduling of jobs. The overall schedule of these jobs is then an emergent behaviour of the strategic interaction of these trading agents bidding for resources in a market based on limited information and their own preferences. Using a simple (zero-intelligence) bidding strategy, we empirically demonstrate that our market-based approach achieves a lower bound efficiency of 84%. This represents a trade-off between a reasonable level of efficiency (compared to a centralised approach) and the desirable benefits of a decentralised solution.

Connectionist agent-based learning in bank-run decision making

NASA Astrophysics Data System (ADS)

Huang, Weihong; Huang, Qiao

2018-05-01

It is of utter importance for the policy makers, bankers, and investors to thoroughly understand the probability of bank-run (PBR) which was often neglected in the classical models. Bank-run is not merely due to miscoordination (Diamond and Dybvig, 1983) or deterioration of bank assets (Allen and Gale, 1998) but various factors. This paper presents the simulation results of the nonlinear dynamic probabilities of bank runs based on the global games approach, with the distinct assumption that heterogenous agents hold highly correlated but unidentical beliefs about the true payoffs. The specific technique used in the simulation is to let agents have an integrated cognitive-affective network. It is observed that, even when the economy is good, agents are significantly affected by the cognitive-affective network to react to bad news which might lead to bank-run. Both the rise of the late payoffs, R, and the early payoffs, r, will decrease the effect of the affective process. The increased risk sharing might or might not increase PBR, and the increase in late payoff is beneficial for preventing the bank run. This paper is one of the pioneers that links agent-based computational economics and behavioral economics.

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.

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.

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.

Remote Data Retrieval for Bioinformatics Applications: An Agent Migration Approach

PubMed Central

Gao, Lei; Dai, Hua; Zhang, Tong-Liang; Chou, Kuo-Chen

2011-01-01

Some of the approaches have been developed to retrieve data automatically from one or multiple remote biological data sources. However, most of them require researchers to remain online and wait for returned results. The latter not only requires highly available network connection, but also may cause the network overload. Moreover, so far none of the existing approaches has been designed to address the following problems when retrieving the remote data in a mobile network environment: (1) the resources of mobile devices are limited; (2) network connection is relatively of low quality; and (3) mobile users are not always online. To address the aforementioned problems, we integrate an agent migration approach with a multi-agent system to overcome the high latency or limited bandwidth problem by moving their computations to the required resources or services. More importantly, the approach is fit for the mobile computing environments. Presented in this paper are also the system architecture, the migration strategy, as well as the security authentication of agent migration. As a demonstration, the remote data retrieval from GenBank was used to illustrate the feasibility of the proposed approach. PMID:21701677

The dynamic influence of human resources on evidence-based intervention sustainability and population outcomes: an agent-based modeling approach.

PubMed

McKay, Virginia R; Hoffer, Lee D; Combs, Todd B; Margaret Dolcini, M

2018-06-05

Sustaining evidence-based interventions (EBIs) is an ongoing challenge for dissemination and implementation science in public health and social services. Characterizing the relationship among human resource capacity within an agency and subsequent population outcomes is an important step to improving our understanding of how EBIs are sustained. Although human resource capacity and population outcomes are theoretically related, examining them over time within real-world experiments is difficult. Simulation approaches, especially agent-based models, offer advantages that complement existing methods. We used an agent-based model to examine the relationships among human resources, EBI delivery, and population outcomes by simulating provision of an EBI through a hypothetical agency and its staff. We used data from existing studies examining a widely implemented HIV prevention intervention to inform simulation design, calibration, and validity. Once we developed a baseline model, we used the model as a simulated laboratory by systematically varying three human resource variables: the number of staff positions, the staff turnover rate, and timing in training. We tracked the subsequent influence on EBI delivery and the level of population risk over time to describe the overall and dynamic relationships among these variables. Higher overall levels of human resource capacity at an agency (more positions) led to more extensive EBI delivery over time and lowered population risk earlier in time. In simulations representing the typical human resource investments, substantial influences on population risk were visible after approximately 2 years and peaked around 4 years. Human resources, especially staff positions, have an important impact on EBI sustainability and ultimately population health. A minimum level of human resources based on the context (e.g., size of the initial population and characteristics of the EBI) is likely needed for an EBI to have a meaningful impact on

Translational systems biology using an agent-based approach for dynamic knowledge representation: An evolutionary paradigm for biomedical research.

PubMed

An, Gary C

2010-01-01

The greatest challenge facing the biomedical research community is the effective translation of basic mechanistic knowledge into clinically effective therapeutics. This challenge is most evident in attempts to understand and modulate "systems" processes/disorders, such as sepsis, cancer, and wound healing. Formulating an investigatory strategy for these issues requires the recognition that these are dynamic processes. Representation of the dynamic behavior of biological systems can aid in the investigation of complex pathophysiological processes by augmenting existing discovery procedures by integrating disparate information sources and knowledge. This approach is termed Translational Systems Biology. Focusing on the development of computational models capturing the behavior of mechanistic hypotheses provides a tool that bridges gaps in the understanding of a disease process by visualizing "thought experiments" to fill those gaps. Agent-based modeling is a computational method particularly well suited to the translation of mechanistic knowledge into a computational framework. Utilizing agent-based models as a means of dynamic hypothesis representation will be a vital means of describing, communicating, and integrating community-wide knowledge. The transparent representation of hypotheses in this dynamic fashion can form the basis of "knowledge ecologies," where selection between competing hypotheses will apply an evolutionary paradigm to the development of community knowledge.

Application of a swarm-based approach for phase unwrapping

NASA Astrophysics Data System (ADS)

da S. Maciel, Lucas; Albertazzi G., Armando, Jr.

2014-07-01

An algorithm for phase unwrapping based on swarm intelligence is proposed. The novel approach is based on the emergent behavior of swarms. This behavior is the result of the interactions between independent agents following a simple set of rules and is regarded as fast, flexible and robust. The rules here were designed with two purposes. Firstly, the collective behavior must result in a reliable map of the unwrapped phase. The unwrapping reliability was evaluated by each agent during run-time, based on the quality of the neighboring pixels. In addition, the rule set must result in a behavior that focuses on wrapped regions. Stigmergy and communication rules were implemented in order to enable each agent to seek less worked areas of the image. The agents were modeled as Finite-State Machines. Based on the availability of unwrappable pixels, each agent assumed a different state in order to better adapt itself to the surroundings. The implemented rule set was able to fulfill the requirements on reliability and focused unwrapping. The unwrapped phase map was comparable to those from established methods as the agents were able to reliably evaluate each pixel quality. Also, the unwrapping behavior, being observed in real time, was able to focus on workable areas as the agents communicated in order to find less traveled regions. The results were very positive for such a new approach to the phase unwrapping problem. Finally, the authors see great potential for future developments concerning the flexibility, robustness and processing times of the swarm-based algorithm.

Dynamical systems approach to the study of a sociophysics agent-based model

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

2011-03-24

The Sznajd model is a Potts-like model that has been studied in the context of sociophysics [1,2](where spins are interpreted as opinions). In a recent work [3], we generalized the Sznajd model to include assymetric interactions between the spins (interpreted as biases towards opinions) and used dynamical systems techniques to tackle its mean-field version, given by the flow: {eta}{sub {sigma}} = {Sigma}{sub {sigma}}'{sup M} = 1{eta}{sub {sigma}}{eta}{sigma}'({eta}{sub {sigma}}{rho}{sigma}'{yields}{sigma}-{sigma}'{rho}{sigma}{yields}{sigma}').Where hs is the proportion of agents with opinion (spin){sigma}', M is the number of opinions and {sigma}'{yields}{sigma}' is the probability weight for an agent with opinion {sigma} being convinced by another agentmore » with opinion {sigma}'. We made Monte Carlo simulations of the model in a complex network (using Barabasi-Albert networks [4]) and they displayed the same attractors than the mean-field. Using linear stability analysis, we were able to determine the mean-field attractor structure analytically and to show that it has connections with well known graph theory problems (maximal independent sets and positive fluxes in directed graphs). Our dynamical systems approach is quite simple and can be used also in other models, like the voter model.« less

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.

Climate Shocks and Migration: An Agent-Based Modeling Approach

PubMed Central

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

2016-01-01

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

Programming secure mobile agents in healthcare environments using role-based permissions.

PubMed

Georgiadis, C K; Baltatzis, J; Pangalos, G I

2003-01-01

The healthcare environment consists of vast amounts of dynamic and unstructured information, distributed over a large number of information systems. Mobile agent technology is having an ever-growing impact on the delivery of medical information. It supports acquiring and manipulating information distributed in a large number of information systems. Moreover is suitable for the computer untrained medical stuff. But the introduction of mobile agents generates advanced threads to the sensitive healthcare information, unless the proper countermeasures are taken. By applying the role-based approach to the authorization problem, we ease the sharing of information between hospital information systems and we reduce the administering part. The different initiative of the agent's migration method, results in different methods of assigning roles to the agent.

A Quantum Approach to Multi-Agent Systems (MAS), Organizations, and Control

DTIC Science & Technology

2003-06-01

interdependent interactions between individuals represented approximately as vocal harmonic I resonators. Then the growth rate of an organization fits ...A quantum approach to multi-agent systems (MAS), organizations , and control W.F. Lawless Paine College 1235 15th Street Augusta, GA 30901...AND SUBTITLE A quantum approach to multi-agent systems (MAS), organizations , and control 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT

Evaluating the effect of human activity patterns on air pollution exposure using an integrated field-based and agent-based modelling framework

NASA Astrophysics Data System (ADS)

Schmitz, Oliver; Beelen, Rob M. J.; de Bakker, Merijn P.; Karssenberg, Derek

2015-04-01

Constructing spatio-temporal numerical models to support risk assessment, such as assessing the exposure of humans to air pollution, often requires the integration of field-based and agent-based modelling approaches. Continuous environmental variables such as air pollution are best represented using the field-based approach which considers phenomena as continuous fields having attribute values at all locations. When calculating human exposure to such pollutants it is, however, preferable to consider the population as a set of individuals each with a particular activity pattern. This would allow to account for the spatio-temporal variation in a pollutant along the space-time paths travelled by individuals, determined, for example, by home and work locations, road network, and travel times. Modelling this activity pattern requires an agent-based or individual based modelling approach. In general, field- and agent-based models are constructed with the help of separate software tools, while both approaches should play together in an interacting way and preferably should be combined into one modelling framework, which would allow for efficient and effective implementation of models by domain specialists. To overcome this lack in integrated modelling frameworks, we aim at the development of concepts and software for an integrated field-based and agent-based modelling framework. Concepts merging field- and agent-based modelling were implemented by extending PCRaster (http://www.pcraster.eu), a field-based modelling library implemented in C++, with components for 1) representation of discrete, mobile, agents, 2) spatial networks and algorithms by integrating the NetworkX library (http://networkx.github.io), allowing therefore to calculate e.g. shortest routes or total transport costs between locations, and 3) functions for field-network interactions, allowing to assign field-based attribute values to networks (i.e. as edge weights), such as aggregated or averaged

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

PubMed

Kim, Minsung; Kim, Minki

2014-01-01

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

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

PubMed Central

Kim, Minsung; Kim, Minki

2014-01-01

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

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

PubMed Central

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

2015-01-01

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. PMID:26158406

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.

Identifying and individuating cognitive systems: a task-based distributed cognition alternative to agent-based extended cognition.

PubMed

Davies, Jim; Michaelian, Kourken

2016-08-01

This article argues for a task-based approach to identifying and individuating cognitive systems. The agent-based extended cognition approach faces a problem of cognitive bloat and has difficulty accommodating both sub-individual cognitive systems ("scaling down") and some supra-individual cognitive systems ("scaling up"). The standard distributed cognition approach can accommodate a wider variety of supra-individual systems but likewise has difficulties with sub-individual systems and faces the problem of cognitive bloat. We develop a task-based variant of distributed cognition designed to scale up and down smoothly while providing a principled means of avoiding cognitive bloat. The advantages of the task-based approach are illustrated by means of two parallel case studies: re-representation in the human visual system and in a biomedical engineering laboratory.

Evolution of and perspectives on therapeutic approaches to nerve agent poisoning.

PubMed

Masson, Patrick

2011-09-25

After more than 70 years of considerable efforts, research on medical defense against nerve agents has come to a standstill. Major progress in medical countermeasures was achieved between the 50s and 70s with the development of anticholinergic drugs and carbamate-based pretreatment, the introduction of pyridinium oximes as antidotes, and benzodiazepines in emergency treatments. These drugs ensure good protection of the peripheral nervous system and mitigate the acute effects of exposure to lethal doses of nerve agents. However, pyridostigmine and cholinesterase reactivators currently used in the armed forces do not protect/reactivate central acetylcholinesterases. Moreover, other drugs used are not sufficiently effective in protecting the central nervous system against seizures, irreversible brain damages and long-term sequelae of nerve agent poisoning.New developments of medical counter-measures focus on: (a) detoxification of organophosphorus molecules before they react with acetylcholinesterase and other physiological targets by administration of stoichiometric or catalytic scavengers; (b) protection and reactivation of central acetylcholinesterases, and (c) improvement of neuroprotection following delayed therapy.Future developments will aim at treatment of acute and long-term effects of low level exposure to nerve agents, research on alternative routes for optimizing drug delivery, and therapies. Though gene therapy for in situ generation of bioscavengers, and cell therapy based on neural progenitor engraftment for neuronal regeneration have been successfully explored, more studies are needed before practical medical applications can be made of these new approaches. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

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.

A Watershed-Scale Agent-Based Model Incorporating Agent Learning and Interaction of Farmers' Decisions Subject to Carbon and Miscanthus Prices

NASA Astrophysics Data System (ADS)

Ng, T.; Eheart, J.; Cai, X.; Braden, J. B.

2010-12-01

Agricultural watersheds are coupled human-natural systems where the land use decisions of human agents (farmers) affect surface water quality, and in turn, are affected by the weather and yields. The reliable modeling of such systems requires an approach that considers both the human and natural aspects. Agent-based modeling (ABM), representing the human aspect, coupled with hydrologic modeling, representing the natural aspect, is one such approach. ABM is a relatively new modeling paradigm that formulates the system from the perspectives of the individual agents, i.e., each agent is modeled as a discrete autonomous entity with distinct goals and actions. The primary objective of this study is to demonstrate the applicability of this approach to agricultural watershed management. This is done using a semi-hypothetical case study of farmers in the Salt Creek watershed in East-Central Illinois under the influence markets for carbon and second-generation bioenergy crop (specifically, miscanthus). An agent-based model of the system is developed and linked to a hydrologic model of the watershed. The former is based on fundamental economic and mathematical programming principles, while the latter is based on the Soil and Water Assessment Tool (SWAT). Carbon and second-generation bioenergy crop markets are of interest here due to climate change and energy independence concerns. The agent-based model is applied to fifty hypothetical heterogeneous farmers. The farmers' decisions depend on their perceptions of future conditions. Those perceptions are updated, according to a pre-defined algorithm, as the farmers make new observations of prices, costs, yields and the weather with time. The perceptions are also updated as the farmers interact with each other as they share new information on initially unfamiliar activities (e.g., carbon trading, miscanthus cultivation). The updating algorithm is set differently for different farmers such that each is unique in his processing of

Strengthening Theoretical Testing in Criminology Using Agent-based Modeling.

PubMed

Johnson, Shane D; Groff, Elizabeth R

2014-07-01

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

A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling.

PubMed

Singh, Karandeep; Ahn, Chang-Won; Paik, Euihyun; Bae, Jang Won; Lee, Chun-Hee

2018-01-01

Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or "soft," aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing. Furthermore, we use this framework to implement a hybrid model using microsimulation and agent-based modeling techniques to generate an artificial society. We leverage this artificial society to simulate and analyze population dynamics using Korean population census data. The agents in this model derive their decisional behaviors from real data (microsimulation feature) and interact among themselves (agent-based modeling feature) to proceed in the simulation. The behaviors, interactions, and social scenarios of the agents are varied to perform an analysis of population dynamics. We also estimate the future cost of pension policies based on the future population structure of the artificial society. The proposed framework and model demonstrates how ALife techniques can be used by researchers in relation to social issues and policies.

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.

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

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.

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

An Approach to Model Based Testing of Multiagent Systems

PubMed Central

Nadeem, Aamer

2015-01-01

Autonomous agents perform on behalf of the user to achieve defined goals or objectives. They are situated in dynamic environment and are able to operate autonomously to achieve their goals. In a multiagent system, agents cooperate with each other to achieve a common goal. Testing of multiagent systems is a challenging task due to the autonomous and proactive behavior of agents. However, testing is required to build confidence into the working of a multiagent system. Prometheus methodology is a commonly used approach to design multiagents systems. Systematic and thorough testing of each interaction is necessary. This paper proposes a novel approach to testing of multiagent systems based on Prometheus design artifacts. In the proposed approach, different interactions between the agent and actors are considered to test the multiagent system. These interactions include percepts and actions along with messages between the agents which can be modeled in a protocol diagram. The protocol diagram is converted into a protocol graph, on which different coverage criteria are applied to generate test paths that cover interactions between the agents. A prototype tool has been developed to generate test paths from protocol graph according to the specified coverage criterion. PMID:25874263

Application of agent-based system for bioprocess description and process improvement.

PubMed

Gao, Ying; Kipling, Katie; Glassey, Jarka; Willis, Mark; Montague, Gary; Zhou, Yuhong; Titchener-Hooker, Nigel J

2010-01-01

Modeling plays an important role in bioprocess development for design and scale-up. Predictive models can also be used in biopharmaceutical manufacturing to assist decision-making either to maintain process consistency or to identify optimal operating conditions. To predict the whole bioprocess performance, the strong interactions present in a processing sequence must be adequately modeled. Traditionally, bioprocess modeling considers process units separately, which makes it difficult to capture the interactions between units. In this work, a systematic framework is developed to analyze the bioprocesses based on a whole process understanding and considering the interactions between process operations. An agent-based approach is adopted to provide a flexible infrastructure for the necessary integration of process models. This enables the prediction of overall process behavior, which can then be applied during process development or once manufacturing has commenced, in both cases leading to the capacity for fast evaluation of process improvement options. The multi-agent system comprises a process knowledge base, process models, and a group of functional agents. In this system, agent components co-operate with each other in performing their tasks. These include the description of the whole process behavior, evaluating process operating conditions, monitoring of the operating processes, predicting critical process performance, and providing guidance to decision-making when coping with process deviations. During process development, the system can be used to evaluate the design space for process operation. During manufacture, the system can be applied to identify abnormal process operation events and then to provide suggestions as to how best to cope with the deviations. In all cases, the function of the system is to ensure an efficient manufacturing process. The implementation of the agent-based approach is illustrated via selected application scenarios, which

Intelligent judgements over health risks in a spatial agent-based model.

PubMed

Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

2018-03-20

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of

Quantitative Analysis of Intra Urban Growth Modeling using socio economic agents by combining cellular automata model with agent based model

NASA Astrophysics Data System (ADS)

Singh, V. K.; Jha, A. K.; Gupta, K.; Srivastav, S. K.

2017-12-01

Recent studies indicate that there is a significant improvement in the urban land use dynamics through modeling at finer spatial resolutions. Geo-computational models such as cellular automata and agent based model have given evident proof regarding the quantification of the urban growth pattern with urban boundary. In recent studies, socio- economic factors such as demography, education rate, household density, parcel price of the current year, distance to road, school, hospital, commercial centers and police station are considered to the major factors influencing the Land Use Land Cover (LULC) pattern of the city. These factors have unidirectional approach to land use pattern which makes it difficult to analyze the spatial aspects of model results both quantitatively and qualitatively. In this study, cellular automata model is combined with generic model known as Agent Based Model to evaluate the impact of socio economic factors on land use pattern. For this purpose, Dehradun an Indian city is selected as a case study. Socio economic factors were collected from field survey, Census of India, Directorate of economic census, Uttarakhand, India. A 3X3 simulating window is used to consider the impact on LULC. Cellular automata model results are examined for the identification of hot spot areas within the urban area and agent based model will be using logistic based regression approach where it will identify the correlation between each factor on LULC and classify the available area into low density, medium density, high density residential or commercial area. In the modeling phase, transition rule, neighborhood effect, cell change factors are used to improve the representation of built-up classes. Significant improvement is observed in the built-up classes from 84 % to 89 %. However after incorporating agent based model with cellular automata model the accuracy improved from 89 % to 94 % in 3 classes of urban i.e. low density, medium density and commercial classes

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.

CATS-based Air Traffic Controller Agents

NASA Technical Reports Server (NTRS)

Callantine, Todd J.

2002-01-01

This report describes intelligent agents that function as air traffic controllers. Each agent controls traffic in a single sector in real time; agents controlling traffic in adjoining sectors can coordinate to manage an arrival flow across a given meter fix. The purpose of this research is threefold. First, it seeks to study the design of agents for controlling complex systems. In particular, it investigates agent planning and reactive control functionality in a dynamic environment in which a variety perceptual and decision making skills play a central role. It examines how heuristic rules can be applied to model planning and decision making skills, rather than attempting to apply optimization methods. Thus, the research attempts to develop intelligent agents that provide an approximation of human air traffic controller behavior that, while not based on an explicit cognitive model, does produce task performance consistent with the way human air traffic controllers operate. Second, this research sought to extend previous research on using the Crew Activity Tracking System (CATS) as the basis for intelligent agents. The agents use a high-level model of air traffic controller activities to structure the control task. To execute an activity in the CATS model, according to the current task context, the agents reference a 'skill library' and 'control rules' that in turn execute the pattern recognition, planning, and decision-making required to perform the activity. Applying the skills enables the agents to modify their representation of the current control situation (i.e., the 'flick' or 'picture'). The updated representation supports the next activity in a cycle of action that, taken as a whole, simulates air traffic controller behavior. A third, practical motivation for this research is to use intelligent agents to support evaluation of new air traffic control (ATC) methods to support new Air Traffic Management (ATM) concepts. Current approaches that use large, human

Derivation of Continuum Models from An Agent-based Cancer Model: Optimization and Sensitivity Analysis.

PubMed

Voulgarelis, Dimitrios; Velayudhan, Ajoy; Smith, Frank

2017-01-01

Agent-based models provide a formidable tool for exploring complex and emergent behaviour of biological systems as well as accurate results but with the drawback of needing a lot of computational power and time for subsequent analysis. On the other hand, equation-based models can more easily be used for complex analysis in a much shorter timescale. This paper formulates an ordinary differential equations and stochastic differential equations model to capture the behaviour of an existing agent-based model of tumour cell reprogramming and applies it to optimization of possible treatment as well as dosage sensitivity analysis. For certain values of the parameter space a close match between the equation-based and agent-based models is achieved. The need for division of labour between the two approaches is explored. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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. Copyright © 2016 Elsevier B.V. All rights reserved.

Agent tracking: a psycho-historical theory of the identification of living and social agents.

PubMed

Bullot, Nicolas J

To explain agent-identification behaviours, universalist theories in the biological and cognitive sciences have posited mental mechanisms thought to be universal to all humans, such as agent detection and face recognition mechanisms. These universalist theories have paid little attention to how particular sociocultural or historical contexts interact with the psychobiological processes of agent-identification. In contrast to universalist theories, contextualist theories appeal to particular historical and sociocultural contexts for explaining agent-identification. Contextualist theories tend to adopt idiographic methods aimed at recording the heterogeneity of human behaviours across history, space, and cultures. Defenders of the universalist approach tend to criticise idiographic methods because such methods can lead to relativism or may lack generality. To overcome explanatory limitations of proposals that adopt either universalist or contextualist approaches in isolation, I propose a philosophical model that integrates contributions from both traditions: the psycho-historical theory of agent-identification. This theory investigates how the tracking processes that humans use for identifying agents interact with the unique socio-historical contexts that support agent-identification practices. In integrating hypotheses about the history of agents with psychological and epistemological principles regarding agent-identification, the theory can generate novel hypotheses regarding the distinction between recognition-based, heuristic-based, and explanation-based agent-identification.

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.

An Approach for Autonomy: A Collaborative Communication Framework for Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Dufrene, Warren Russell, Jr.

2005-01-01

Research done during the last three years has studied the emersion properties of Complex Adaptive Systems (CAS). The deployment of Artificial Intelligence (AI) techniques applied to remote Unmanned Aerial Vehicles has led the author to investigate applications of CAS within the field of Autonomous Multi-Agent Systems. The core objective of current research efforts is focused on the simplicity of Intelligent Agents (IA) and the modeling of these agents within complex systems. This research effort looks at the communication, interaction, and adaptability of multi-agents as applied to complex systems control. The embodiment concept applied to robotics has application possibilities within multi-agent frameworks. A new framework for agent awareness within a virtual 3D world concept is possible where the vehicle is composed of collaborative agents. This approach has many possibilities for applications to complex systems. This paper describes the development of an approach to apply this virtual framework to the NASA Goddard Space Flight Center (GSFC) tetrahedron structure developed under the Autonomous Nano Technology Swarm (ANTS) program and the Super Miniaturized Addressable Reconfigurable Technology (SMART) architecture program. These projects represent an innovative set of novel concepts deploying adaptable, self-organizing structures composed of many tetrahedrons. This technology is pushing current applied Agents Concepts to new levels of requirements and adaptability.

Multi-agent systems: effective approach for cancer care information management.

PubMed

Mohammadzadeh, Niloofar; Safdari, Reza; Rahimi, Azin

2013-01-01

Physicians, in order to study the causes of cancer, detect cancer earlier, prevent or determine the effectiveness of treatment, and specify the reasons for the treatment ineffectiveness, need to access accurate, comprehensive, and timely cancer data. The cancer care environment has become more complex because of the need for coordination and communication among health care professionals with different skills in a variety of roles and the existence of large amounts of data with various formats. The goals of health care systems in such a complex environment are correct health data management, providing appropriate information needs of users to enhance the integrity and quality of health care, timely access to accurate information and reducing medical errors. These roles in new systems with use of agents efficiently perform well. Because of the potential capability of agent systems to solve complex and dynamic health problems, health care system, in order to gain full advantage of E- health, steps must be taken to make use of this technology. Multi-agent systems have effective roles in health service quality improvement especially in telemedicine, emergency situations and management of chronic diseases such as cancer. In the design and implementation of agent based systems, planning items such as information confidentiality and privacy, architecture, communication standards, ethical and legal aspects, identification opportunities and barriers should be considered. It should be noted that usage of agent systems only with a technical view is associated with many problems such as lack of user acceptance. The aim of this commentary is to survey applications, opportunities and barriers of this new artificial intelligence tool for cancer care information as an approach to improve cancer care management.

Word of Mouth : An Agent-based Approach to Predictability of Stock Prices

NASA Astrophysics Data System (ADS)

Shimokawa, Tetsuya; Misawa, Tadanobu; Watanabe, Kyoko

This paper addresses how communication processes among investors affect stock prices formation, especially emerging predictability of stock prices, in financial markets. An agent based model, called the word of mouth model, is introduced for analyzing the problem. This model provides a simple, but sufficiently versatile, description of informational diffusion process and is successful in making lucidly explanation for the predictability of small sized stocks, which is a stylized fact in financial markets but difficult to resolve by traditional models. Our model also provides a rigorous examination of the under reaction hypothesis to informational shocks.

Agent-based user-adaptive service provision in ubiquitous systems

NASA Astrophysics Data System (ADS)

Saddiki, H.; Harroud, H.; Karmouch, A.

2012-11-01

With the increasing availability of smartphones, tablets and other computing devices, technology consumers have grown accustomed to performing all of their computing tasks anytime, anywhere and on any device. There is a greater need to support ubiquitous connectivity and accommodate users by providing software as network-accessible services. In this paper, we propose a MAS-based approach to adaptive service composition and provision that automates the selection and execution of a suitable composition plan for a given service. With agents capable of autonomous and intelligent behavior, the composition plan is selected in a dynamic negotiation driven by a utility-based decision-making mechanism; and the composite service is built by a coalition of agents each providing a component necessary to the target service. The same service can be built in variations for catering to dynamic user contexts and further personalizing the user experience. Also multiple services can be grouped to satisfy new user needs.

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

PubMed

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

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

Multi-issue Agent Negotiation Based on Fairness

NASA Astrophysics Data System (ADS)

Zuo, Baohe; Zheng, Sue; Wu, Hong

Agent-based e-commerce service has become a hotspot now. How to make the agent negotiation process quickly and high-efficiently is the main research direction of this area. In the multi-issue model, MAUT(Multi-attribute Utility Theory) or its derived theory usually consider little about the fairness of both negotiators. This work presents a general model of agent negotiation which considered the satisfaction of both negotiators via autonomous learning. The model can evaluate offers from the opponent agent based on the satisfaction degree, learn online to get the opponent's knowledge from interactive instances of history and negotiation of this time, make concessions dynamically based on fair object. Through building the optimal negotiation model, the bilateral negotiation achieved a higher efficiency and fairer deal.

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.

AGENT-BASED MODELING OF INDUSTRIAL ECOSYSTEMS

EPA Science Inventory

The objectives of this research are to investigate behavioral and organizational questions associated with environmental regulation of firms, and to test specifically whether a bottom-up approach that highlights principal-agent problems offers new insights and empirical validi...

Towards a complex systems approach in sports injury research: simulating running-related injury development with agent-based modelling.

PubMed

Hulme, Adam; Thompson, Jason; Nielsen, Rasmus Oestergaard; Read, Gemma J M; Salmon, Paul M

2018-06-18

There have been recent calls for the application of the complex systems approach in sports injury research. However, beyond theoretical description and static models of complexity, little progress has been made towards formalising this approach in way that is practical to sports injury scientists and clinicians. Therefore, our objective was to use a computational modelling method and develop a dynamic simulation in sports injury research. Agent-based modelling (ABM) was used to model the occurrence of sports injury in a synthetic athlete population. The ABM was developed based on sports injury causal frameworks and was applied in the context of distance running-related injury (RRI). Using the acute:chronic workload ratio (ACWR), we simulated the dynamic relationship between changes in weekly running distance and RRI through the manipulation of various 'athlete management tools'. The findings confirmed that building weekly running distances over time, even within the reported ACWR 'sweet spot', will eventually result in RRI as athletes reach and surpass their individual physical workload limits. Introducing training-related error into the simulation and the modelling of a 'hard ceiling' dynamic resulted in a higher RRI incidence proportion across the population at higher absolute workloads. The presented simulation offers a practical starting point to further apply more sophisticated computational models that can account for the complex nature of sports injury aetiology. Alongside traditional forms of scientific inquiry, the use of ABM and other simulation-based techniques could be considered as a complementary and alternative methodological approach in sports injury research. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Evolutionary Agent-based Models to design distributed water management strategies

NASA Astrophysics Data System (ADS)

Giuliani, M.; Castelletti, A.; Reed, P. M.

2012-12-01

There is growing awareness in the scientific community that the traditional centralized approach to water resources management, as described in much of the water resources literature, provides an ideal optimal solution, which is certainly useful to quantify the best physically achievable performance, but is generally inapplicable. Most real world water resources management problems are indeed characterized by the presence of multiple, distributed and institutionally-independent decision-makers. Multi-Agent Systems provide a potentially more realistic alternative framework to model multiple and self-interested decision-makers in a credible context. Each decision-maker can be represented by an agent who, being self-interested, acts according to local objective functions and produces negative externalities on system level objectives. Different levels of coordination can potentially be included in the framework by designing coordination mechanisms to drive the current decision-making structure toward the global system efficiency. Yet, the identification of effective coordination strategies can be particularly complex in modern institutional contexts and current practice is dependent on largely ad-hoc coordination strategies. In this work we propose a novel Evolutionary Agent-based Modeling (EAM) framework that enables a mapping of fully uncoordinated and centrally coordinated solutions into their relative "many-objective" tradeoffs using multiobjective evolutionary algorithms. Then, by analysing the conflicts between local individual agent and global system level objectives it is possible to more fully understand the causes, consequences, and potential solution strategies for coordination failures. Game-theoretic criteria have value for identifying the most interesting alternatives from a policy making point of view as well as the coordination mechanisms that can be applied to obtain these interesting solutions. The proposed approach is numerically tested on a

A Distributed, Collaborative Intelligent Agent System Approach for Proactive Postmarketing Drug Safety Surveillance

PubMed Central

Ji, Yanqing; Ying, Hao; Farber, Margo S.; Yen, John; Dews, Peter; Miller, Richard E.; Massanari, R. Michael

2014-01-01

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is of great importance. The current approach to postmarketing surveillance primarily relies on spontaneous reporting. It is a passive surveillance system and limited by gross underreporting (<10% reporting rate), latency, and inconsistent reporting. We propose a novel team-based intelligent agent software system approach for proactively monitoring and detecting potential ADRs of interest using electronic patient records. We designed such a system and named it ADRMonitor. The intelligent agents, operating on computers located in different places, are capable of continuously and autonomously collaborating with each other and assisting the human users (e.g., the food and drug administration (FDA), drug safety professionals, and physicians). The agents should enhance current systems and accelerate early ADR identification. To evaluate the performance of the ADRMonitor with respect to the current spontaneous reporting approach, we conducted simulation experiments on identification of ADR signal pairs (i.e., potential links between drugs and apparent adverse reactions) under various conditions. The experiments involved over 275 000 simulated patients created on the basis of more than 1000 real patients treated by the drug cisapride that was on the market for seven years until its withdrawal by the FDA in 2000 due to serious ADRs. Healthcare professionals utilizing the spontaneous reporting approach and the ADRMonitor were separately simulated by decision-making models derived from a general cognitive decision model called fuzzy recognition-primed decision (RPD) model that we recently developed. The quantitative simulation results show that 1) the number of true ADR signal pairs detected by the ADRMonitor is 6.6 times higher than that by the spontaneous reporting strategy; 2) the ADR detection rate of the ADRMonitor agents with even moderate decision-making skills is five

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.

Agent-based models of cellular systems.

PubMed

Cannata, Nicola; Corradini, Flavio; Merelli, Emanuela; Tesei, Luca

2013-01-01

Software agents are particularly suitable for engineering models and simulations of cellular systems. In a very natural and intuitive manner, individual software components are therein delegated to reproduce "in silico" the behavior of individual components of alive systems at a given level of resolution. Individuals' actions and interactions among individuals allow complex collective behavior to emerge. In this chapter we first introduce the readers to software agents and multi-agent systems, reviewing the evolution of agent-based modeling of biomolecular systems in the last decade. We then describe the main tools, platforms, and methodologies available for programming societies of agents, possibly profiting also of toolkits that do not require advanced programming skills.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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.

An Immune Agent for Web-Based AI Course

ERIC Educational Resources Information Center

Gong, Tao; Cai, Zixing

2006-01-01

To overcome weakness and faults of a web-based e-learning course such as Artificial Intelligence (AI), an immune agent was proposed, simulating a natural immune mechanism against a virus. The immune agent was built on the multi-dimension education agent model and immune algorithm. The web-based AI course was comprised of many files, such as HTML…

Can agent based models effectively reduce fisheries management implementation uncertainty?

NASA Astrophysics Data System (ADS)

Drexler, M.

2016-02-01

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

A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning.

PubMed

Chung, Michael Jae-Yoon; Friesen, Abram L; Fox, Dieter; Meltzoff, Andrew N; Rao, Rajesh P N

2015-01-01

A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i) learn probabilistic models of actions through self-discovery and experience, (ii) utilize these learned models for inferring the goals of human actions, and (iii) perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i) a simulated robot that learns human-like gaze following behavior, and (ii) a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration.

Melanin-Based Contrast Agents for Biomedical Optoacoustic Imaging and Theranostic Applications.

PubMed

Longo, Dario Livio; Stefania, Rachele; Aime, Silvio; Oraevsky, Alexander

2017-08-07

Optoacoustic imaging emerged in early 1990s as a new biomedical imaging technology that generates images by illuminating tissues with short laser pulses and detecting resulting ultrasound waves. This technique takes advantage of the spectroscopic approach to molecular imaging, and delivers high-resolution images in the depth of tissue. Resolution of the optoacoustic imaging is scalable, so that biomedical systems from cellular organelles to large organs can be visualized and, more importantly, characterized based on their optical absorption coefficient, which is proportional to the concentration of absorbing chromophores. Optoacoustic imaging was shown to be useful in both preclinical research using small animal models and in clinical applications. Applications in the field of molecular imaging offer abundant opportunities for the development of highly specific and effective contrast agents for quantitative optoacoustic imaging. Recent efforts are being made in the direction of nontoxic biodegradable contrast agents (such as nanoparticles made of melanin) that are potentially applicable in clinical optoacoustic imaging. In order to increase the efficiency and specificity of contrast agents and probes, they need to be made smart and capable of controlled accumulation in the target cells. This review was written in recognition of the potential breakthroughs in medical optoacoustic imaging that can be enabled by efficient and nontoxic melanin-based optoacoustic contrast agents.

Melanin-Based Contrast Agents for Biomedical Optoacoustic Imaging and Theranostic Applications

PubMed Central

Longo, Dario Livio; Aime, Silvio

2017-01-01

Optoacoustic imaging emerged in early 1990s as a new biomedical imaging technology that generates images by illuminating tissues with short laser pulses and detecting resulting ultrasound waves. This technique takes advantage of the spectroscopic approach to molecular imaging, and delivers high-resolution images in the depth of tissue. Resolution of the optoacoustic imaging is scalable, so that biomedical systems from cellular organelles to large organs can be visualized and, more importantly, characterized based on their optical absorption coefficient, which is proportional to the concentration of absorbing chromophores. Optoacoustic imaging was shown to be useful in both preclinical research using small animal models and in clinical applications. Applications in the field of molecular imaging offer abundant opportunities for the development of highly specific and effective contrast agents for quantitative optoacoustic imaging. Recent efforts are being made in the direction of nontoxic biodegradable contrast agents (such as nanoparticles made of melanin) that are potentially applicable in clinical optoacoustic imaging. In order to increase the efficiency and specificity of contrast agents and probes, they need to be made smart and capable of controlled accumulation in the target cells. This review was written in recognition of the potential breakthroughs in medical optoacoustic imaging that can be enabled by efficient and nontoxic melanin-based optoacoustic contrast agents. PMID:28783106

A technology path to tactical agent-based modeling

NASA Astrophysics Data System (ADS)

James, Alex; Hanratty, Timothy P.

2017-05-01

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

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

PubMed Central

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

2015-01-01

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

A mobile agent-based moving objects indexing algorithm in location based service

NASA Astrophysics Data System (ADS)

Fang, Zhixiang; Li, Qingquan; Xu, Hong

2006-10-01

This paper will extends the advantages of location based service, specifically using their ability to management and indexing the positions of moving object, Moreover with this objective in mind, a mobile agent-based moving objects indexing algorithm is proposed in this paper to efficiently process indexing request and acclimatize itself to limitation of location based service environment. The prominent feature of this structure is viewing moving object's behavior as the mobile agent's span, the unique mapping between the geographical position of moving objects and span point of mobile agent is built to maintain the close relationship of them, and is significant clue for mobile agent-based moving objects indexing to tracking moving objects.

A market-based optimization approach to sensor and resource management

NASA Astrophysics Data System (ADS)

Schrage, Dan; Farnham, Christopher; Gonsalves, Paul G.

2006-05-01

Dynamic resource allocation for sensor management is a problem that demands solutions beyond traditional approaches to optimization. Market-based optimization applies solutions from economic theory, particularly game theory, to the resource allocation problem by creating an artificial market for sensor information and computational resources. Intelligent agents are the buyers and sellers in this market, and they represent all the elements of the sensor network, from sensors to sensor platforms to computational resources. These agents interact based on a negotiation mechanism that determines their bidding strategies. This negotiation mechanism and the agents' bidding strategies are based on game theory, and they are designed so that the aggregate result of the multi-agent negotiation process is a market in competitive equilibrium, which guarantees an optimal allocation of resources throughout the sensor network. This paper makes two contributions to the field of market-based optimization: First, we develop a market protocol to handle heterogeneous goods in a dynamic setting. Second, we develop arbitrage agents to improve the efficiency in the market in light of its dynamic nature.

Emerging medical informatics with case-based reasoning for aiding clinical decision in multi-agent system.

PubMed

Shen, Ying; Colloc, Joël; Jacquet-Andrieu, Armelle; Lei, Kai

2015-08-01

This research aims to depict the methodological steps and tools about the combined operation of case-based reasoning (CBR) and multi-agent system (MAS) to expose the ontological application in the field of clinical decision support. The multi-agent architecture works for the consideration of the whole cycle of clinical decision-making adaptable to many medical aspects such as the diagnosis, prognosis, treatment, therapeutic monitoring of gastric cancer. In the multi-agent architecture, the ontological agent type employs the domain knowledge to ease the extraction of similar clinical cases and provide treatment suggestions to patients and physicians. Ontological agent is used for the extension of domain hierarchy and the interpretation of input requests. Case-based reasoning memorizes and restores experience data for solving similar problems, with the help of matching approach and defined interfaces of ontologies. A typical case is developed to illustrate the implementation of the knowledge acquisition and restitution of medical experts. Copyright © 2015 Elsevier Inc. All rights reserved.

Enhanced situational awareness in the maritime domain: an agent-based approach for situation management

NASA Astrophysics Data System (ADS)

Brax, Christoffer; Niklasson, Lars

2009-05-01

Maritime Domain Awareness is important for both civilian and military applications. An important part of MDA is detection of unusual vessel activities such as piracy, smuggling, poaching, collisions, etc. Today's interconnected sensorsystems provide us with huge amounts of information over large geographical areas which can make the operators reach their cognitive capacity and start to miss important events. We propose and agent-based situation management system that automatically analyse sensor information to detect unusual activity and anomalies. The system combines knowledge-based detection with data-driven anomaly detection. The system is evaluated using information from both radar and AIS sensors.

Constructing Knowledge with an Agent-Based Instructional Program: A Comparison of Cooperative and Individual Meaning Making

ERIC Educational Resources Information Center

Moreno, Roxana

2009-01-01

Participants in the present study were 87 college students who learned about botany using an agent-based instructional program with three different learning approaches: individual, jigsaw, or cooperative learning. Results showed no differences among learning approaches on retention. Students in jigsaw groups reported higher cognitive load during…

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

Gadolinium-Based Contrast Agents for MR Cancer Imaging

PubMed Central

Zhou, Zhuxian; Lu, Zheng-Rong

2013-01-01

Magnetic resonance imaging (MRI) is a clinical imaging modality effective for anatomical and functional imaging of diseased soft tissues, including solid tumors. MRI contrast agents have been routinely used for detecting tumor at an early stage. Gadolinium based contrast agents are the most commonly used contrast agents in clinical MRI. There have been significant efforts to design and develop novel Gd(III) contrast agents with high relaxivity, low toxicity and specific tumor binding. The relaxivity of the Gd(III) contrast agents can be increased by proper chemical modification. The toxicity of Gd(III) contrast agents can be reduced by increasing the agents’ thermodynamic and kinetic stability, as well as optimizing their pharmacokinetic properties. The increasing knowledge in the field of cancer genomics and biology provides an opportunity for designing tumor-specific contrast agents. Various new Gd(III) chelates have been designed and evaluated in animal models for more effective cancer MRI. This review outlines the design and development, physicochemical properties, and in vivo properties of several classes of Gd(III)-based MR contrast agents for tumor imaging. PMID:23047730

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.

Modeling Protective Anti-Tumor Immunity via Preventative Cancer Vaccines Using a Hybrid Agent-based and Delay Differential Equation Approach

PubMed Central

Kim, Peter S.; Lee, Peter P.

2012-01-01

A next generation approach to cancer envisions developing preventative vaccinations to stimulate a person's immune cells, particularly cytotoxic T lymphocytes (CTLs), to eliminate incipient tumors before clinical detection. The purpose of our study is to quantitatively assess whether such an approach would be feasible, and if so, how many anti-cancer CTLs would have to be primed against tumor antigen to provide significant protection. To understand the relevant dynamics, we develop a two-compartment model of tumor-immune interactions at the tumor site and the draining lymph node. We model interactions at the tumor site using an agent-based model (ABM) and dynamics in the lymph node using a system of delay differential equations (DDEs). We combine the models into a hybrid ABM-DDE system and investigate dynamics over a wide range of parameters, including cell proliferation rates, tumor antigenicity, CTL recruitment times, and initial memory CTL populations. Our results indicate that an anti-cancer memory CTL pool of 3% or less can successfully eradicate a tumor population over a wide range of model parameters, implying that a vaccination approach is feasible. In addition, sensitivity analysis of our model reveals conditions that will result in rapid tumor destruction, oscillation, and polynomial rather than exponential decline in the tumor population due to tumor geometry. PMID:23133347

A Graphical Approach to the Standard Principal-Agent Model.

ERIC Educational Resources Information Center

Zhou, Xianming

2002-01-01

States the principal-agent theory is difficult to teach because of its technical complexity and intractability. Indicates the equilibrium in the contract space is defined by the incentive parameter and insurance component of pay under a linear contract. Describes a graphical approach that students with basic knowledge of algebra and…

A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning

PubMed Central

Chung, Michael Jae-Yoon; Friesen, Abram L.; Fox, Dieter; Meltzoff, Andrew N.; Rao, Rajesh P. N.

2015-01-01

A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i) learn probabilistic models of actions through self-discovery and experience, (ii) utilize these learned models for inferring the goals of human actions, and (iii) perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i) a simulated robot that learns human-like gaze following behavior, and (ii) a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration. PMID:26536366

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…

Multi-agent cooperation pursuit based on an extension of AALAADIN organisational model

NASA Astrophysics Data System (ADS)

Souidi, Mohammed El Habib; Songhao, Piao; Guo, Li; Lin, Chang

2016-11-01

An approach of cooperative pursuit for multiple mobile targets based on multi-agents system is discussed. In this kind of problem the pursuit process is divided into two kinds of tasks. The first one (coalition problem) is designed to solve the problem of the pursuit team formation. To achieve this mission, we used an innovative method based on a dynamic organisation and reorganisation of the pursuers' groups. We introduce our coalition strategy extended from the organisational agent, group, role model by assigning an access mechanism to the groups inspired by fuzzy logic principles. The second task (motion problem) is the treatment of the pursuers' motion strategy. To manage this problem we applied the principles of the Markov decision process. Simulation results show the feasibility and validity of the given proposal.

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.

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

PubMed

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

2015-04-01

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

Integrated PK-PD and Agent-Based Modeling in Oncology

PubMed Central

Wang, Zhihui; Butner, Joseph D.; Cristini, Vittorio

2016-01-01

Mathematical modeling has become a valuable tool that strives to complement conventional biomedical research modalities in order to predict experimental outcome, generate new medical hypotheses, and optimize clinical therapies. Two specific approaches, pharmacokinetic-pharmacodynamic (PK-PD) modeling, and agent-based modeling (ABM), have been widely applied in cancer research. While they have made important contributions on their own (e.g., PK-PD in examining chemotherapy drug efficacy and resistance, and ABM in describing and predicting tumor growth and metastasis), only a few groups have started to combine both approaches together in an effort to gain more insights into the details of drug dynamics and the resulting impact on tumor growth. In this review, we focus our discussion on some of the most recent modeling studies building on a combined PK-PD and ABM approach that have generated experimentally testable hypotheses. Some future directions are also discussed. PMID:25588379

IPA (v1): a framework for agent-based modelling of soil water movement

NASA Astrophysics Data System (ADS)

Mewes, Benjamin; Schumann, Andreas H.

2018-06-01

In the last decade, agent-based modelling (ABM) became a popular modelling technique in social sciences, medicine, biology, and ecology. ABM was designed to simulate systems that are highly dynamic and sensitive to small variations in their composition and their state. As hydrological systems, and natural systems in general, often show dynamic and non-linear behaviour, ABM can be an appropriate way to model these systems. Nevertheless, only a few studies have utilized the ABM method for process-based modelling in hydrology. The percolation of water through the unsaturated soil is highly responsive to the current state of the soil system; small variations in composition lead to major changes in the transport system. Hence, we present a new approach for modelling the movement of water through a soil column: autonomous water agents that transport water through the soil while interacting with their environment as well as with other agents under physical laws.

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.

Internet-enabled collaborative agent-based supply chains

NASA Astrophysics Data System (ADS)

Shen, Weiming; Kremer, Rob; Norrie, Douglas H.

2000-12-01

This paper presents some results of our recent research work related to the development of a new Collaborative Agent System Architecture (CASA) and an Infrastructure for Collaborative Agent Systems (ICAS). Initially being proposed as a general architecture for Internet based collaborative agent systems (particularly complex industrial collaborative agent systems), the proposed architecture is very suitable for managing the Internet enabled complex supply chain for a large manufacturing enterprise. The general collaborative agent system architecture with the basic communication and cooperation services, domain independent components, prototypes and mechanisms are described. Benefits of implementing Internet enabled supply chains with the proposed infrastructure are discussed. A case study on Internet enabled supply chain management is presented.

Agent-Based Models in Social Physics

NASA Astrophysics Data System (ADS)

Quang, Le Anh; Jung, Nam; Cho, Eun Sung; Choi, Jae Han; Lee, Jae Woo

2018-06-01

We review the agent-based models (ABM) on social physics including econophysics. The ABM consists of agent, system space, and external environment. The agent is autonomous and decides his/her behavior by interacting with the neighbors or the external environment with the rules of behavior. Agents are irrational because they have only limited information when they make decisions. They adapt using learning from past memories. Agents have various attributes and are heterogeneous. ABM is a non-equilibrium complex system that exhibits various emergence phenomena. The social complexity ABM describes human behavioral characteristics. In ABMs of econophysics, we introduce the Sugarscape model and the artificial market models. We review minority games and majority games in ABMs of game theory. Social flow ABM introduces crowding, evacuation, traffic congestion, and pedestrian dynamics. We also review ABM for opinion dynamics and voter model. We discuss features and advantages and disadvantages of Netlogo, Repast, Swarm, and Mason, which are representative platforms for implementing ABM.

Static force field representation of environments based on agents' nonlinear motions

NASA Astrophysics Data System (ADS)

Campo, Damian; Betancourt, Alejandro; Marcenaro, Lucio; Regazzoni, Carlo

2017-12-01

This paper presents a methodology that aims at the incremental representation of areas inside environments in terms of attractive forces. It is proposed a parametric representation of velocity fields ruling the dynamics of moving agents. It is assumed that attractive spots in the environment are responsible for modifying the motion of agents. A switching model is used to describe near and far velocity fields, which in turn are used to learn attractive characteristics of environments. The effect of such areas is considered radial over all the scene. Based on the estimation of attractive areas, a map that describes their effects in terms of their localizations, ranges of action, and intensities is derived in an online way. Information of static attractive areas is added dynamically into a set of filters that describes possible interactions between moving agents and an environment. The proposed approach is first evaluated on synthetic data; posteriorly, the method is applied on real trajectories coming from moving pedestrians in an indoor environment.

An agent-based computational model of the spread of tuberculosis

NASA Astrophysics Data System (ADS)

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

2011-05-01

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

Towards a genetics-based adaptive agent to support flight testing

NASA Astrophysics Data System (ADS)

Cribbs, Henry Brown, III

Although the benefits of aircraft simulation have been known since the late 1960s, simulation almost always entails interaction with a human test pilot. This "pilot-in-the-loop" simulation process provides useful evaluative information to the aircraft designer and provides a training tool to the pilot. Emulation of a pilot during the early phases of the aircraft design process might provide designers a useful evaluative tool. Machine learning might emulate a pilot in a simulated aircraft/cockpit setting. Preliminary work in the application of machine learning techniques, such as reinforcement learning, to aircraft maneuvering have shown promise. These studies used simplified interfaces between machine learning agent and the aircraft simulation. The simulations employed low order equivalent system models. High-fidelity aircraft simulations exist, such as the simulations developed by NASA at its Dryden Flight Research Center. To expand the applicational domain of reinforcement learning to aircraft designs, this study presents a series of experiments that examine a reinforcement learning agent in the role of test pilot. The NASA X-31 and F-106 high-fidelity simulations provide realistic aircraft for the agent to maneuver. The approach of the study is to examine an agent possessing a genetic-based, artificial neural network to approximate long-term, expected cost (Bellman value) in a basic maneuvering task. The experiments evaluate different learning methods based on a common feedback function and an identical task. The learning methods evaluated are: Q-learning, Q(lambda)-learning, SARSA learning, and SARSA(lambda) learning. Experimental results indicate that, while prediction error remain quite high, similar, repeatable behaviors occur in both aircraft. Similar behavior exhibits portability of the agent between aircraft with different handling qualities (dynamics). Besides the adaptive behavior aspects of the study, the genetic algorithm used in the agent is shown to

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gallo, Giulia

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.more » 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.« less

The potential of a fluorescent-based approach for bioassay of antifungal agents against chili anthracnose disease in Thailand.

PubMed

Chutrakul, Chanikul; Khaokhajorn, Pratoomporn; Auncharoen, Patchanee; Boonruengprapa, Tanapong; Mongkolporn, Orarat

2013-01-01

Severe chili anthracnose disease in Thailand is caused by Colletotrichum gloeosporioides and C. capsici. To discover anti-anthracnose substances we developed an efficient dual-fluorescent labeling bioassay based on a microdilution approach. Indicator strains used in the assay were constructed by integrating synthetic green fluorescent protein (sGFP) and Discosoma sp. red fluorescent protein (DsRedExp) genes into the genomes of C. gloeosporioides or C. capsici respectively. Survival of co-spore cultures in the presence of inhibitors was determined by the expression levels of these fluorescent proteins. This developed assay has high potential for utilization in the investigation of selective inhibition activity to either one of the pathogens as well as the broad-range inhibitory effect against both pathogens. The value of using the dual-fluorescent assay is rapid, reliable, and consistent identification of anti-anthracnose agents. Most of all, the assay enables the identification of specific inhibitors under the co-cultivation condition.

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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 systemmore » design, and integration of wind power in a smart grid.« less

PEGylated Peptide-Based Imaging Agents for Targeted Molecular Imaging.

PubMed

Wu, Huizi; Huang, Jiaguo

2016-01-01

Molecular imaging is able to directly visualize targets and characterize cellular pathways with a high signal/background ratio, which requires a sufficient amount of agents to uptake and accumulate in the imaging area. The design and development of peptide based agents for imaging and diagnosis as a hot and promising research topic that is booming in the field of molecular imaging. To date, selected peptides have been increasingly developed as agents by coupling with different imaging moieties (such as radiometals and fluorophore) with the help of sophisticated chemical techniques. Although a few successes have been achieved, most of them have failed mainly caused by their fast renal clearance and therefore low tumor uptakes, which may limit the effectively tumor retention effect. Besides, several peptide agents based on nanoparticles have also been developed for medical diagnostics. However, a great majority of those agents shown long circulation times and accumulation over time into the reticuloendothelial system (RES; including spleen, liver, lymph nodes and bone marrow) after systematic administration, such long-term severe accumulation probably results in the possible likelihood of toxicity and potentially induces health hazards. Recently reported design criteria have been proposed not only to enhance binding affinity in tumor region with long retention, but also to improve clearance from the body in a reasonable amount of time. PEGylation has been considered as one of the most successful modification methods to prolong tumor retention and improve the pharmacokinetic and pharmacodynamic properties for peptide-based imaging agents. This review summarizes an overview of PEGylated peptides imaging agents based on different imaging moieties including radioisotopes, fluorophores, and nanoparticles. The unique concepts and applications of various PEGylated peptide-based imaging agents are introduced for each of several imaging moieties. Effects of PEGylation on

The selection of adhesive systems for resin-based luting agents.

PubMed

Carville, Rebecca; Quinn, Frank

2008-01-01

The use of resin-based luting agents is ever expanding with the development of adhesive dentistry. A multitude of different adhesive systems are used with resin-based luting agents, and new products are introduced to the market frequently. Traditional adhesives generally required a multiple step bonding procedure prior to cementing with active resin-based luting materials; however, combined agents offer a simple application procedure. Self-etching 'all-in-one' systems claim that there is no need for the use of a separate adhesive process. The following review addresses the advantages and disadvantages of the available adhesive systems used with resin-based luting agents.

Macromolecular and Dendrimer Based Magnetic Resonance Contrast Agents

PubMed Central

Bumb, Ambika; Brechbiel, Martin W.; Choyke, Peter

2010-01-01

Magnetic resonance imaging (MRI) is a powerful imaging modality that can provide an assessment of function or molecular expression in tandem with anatomic detail. Over the last 20–25 years, a number of gadolinium based MR contrast agents have been developed to enhance signal by altering proton relaxation properties. This review explores a range of these agents from small molecule chelates, such as Gd-DTPA and Gd-DOTA, to macromolecular structures composed of albumin, polylysine, polysaccharides (dextran, inulin, starch), poly(ethylene glycol), copolymers of cystamine and cystine with GD-DTPA, and various dendritic structures based on polyamidoamine and polylysine (Gadomers). The synthesis, structure, biodistribution and targeting of dendrimer-based MR contrast agents are also discussed. PMID:20590365

Agent-based simulation for human-induced hazard analysis.

PubMed

Bulleit, William M; Drewek, Matthew W

2011-02-01

Terrorism could be treated as a hazard for design purposes. For instance, the terrorist hazard could be analyzed in a manner similar to the way that seismic hazard is handled. No matter how terrorism is dealt with in the design of systems, the need for predictions of the frequency and magnitude of the hazard will be required. And, if the human-induced hazard is to be designed for in a manner analogous to natural hazards, then the predictions should be probabilistic in nature. The model described in this article is a prototype model that used agent-based modeling (ABM) to analyze terrorist attacks. The basic approach in this article of using ABM to model human-induced hazards has been preliminarily validated in the sense that the attack magnitudes seem to be power-law distributed and attacks occur mostly in regions where high levels of wealth pass through, such as transit routes and markets. The model developed in this study indicates that ABM is a viable approach to modeling socioeconomic-based infrastructure systems for engineering design to deal with human-induced hazards. © 2010 Society for Risk Analysis.

Peptide Based Radiopharmaceuticals: Specific Construct Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Som, P; Rhodes, B A; Sharma, S S

1997-10-21

The objective of this project was to develop receptor based peptides for diagnostic imaging and therapy. A series of peptides related to cell adhesion molecules (CAM) and immune regulation were designed for radiolabeling with 99mTc and evaluated in animal models as potential diagnostic imaging agents for various disease conditions such as thrombus (clot), acute kidney failure, and inflection/inflammation imaging. The peptides for this project were designed by the industrial partner, Palatin Technologies, (formerly Rhomed, Inc.) using various peptide design approaches including a newly developed rational computer assisted drug design (CADD) approach termed MIDAS (Metal ion Induced Distinctive Array of Structures).more » In this approach, the biological function domain and the 99mTc complexing domain are fused together so that structurally these domains are indistinguishable. This approach allows construction of conformationally rigid metallo-peptide molecules (similar to cyclic peptides) that are metabolically stable in-vivo. All the newly designed peptides were screened in various in vitro receptor binding and functional assays to identify a lead compound. The lead compounds were formulated in a one-step 99mTc labeling kit form which were studied by BNL for detailed in-vivo imaging using various animals models of human disease. Two main peptides usingMIDAS approach evolved and were investigated: RGD peptide for acute renal failure and an immunomodulatory peptide derived from tuftsin (RMT-1) for infection/inflammation imaging. Various RGD based metallopeptides were designed, synthesized and assayed for their efficacy in inhibiting ADP-induced human platelet aggregation. Most of these peptides displayed biological activity in the 1-100 µM range. Based on previous work by others, RGD-I and RGD-II were evaluated in animal models of acute renal failure. These earlier studies showed that after acute ischemic injury the renal cortex displays RGD receptor with higher

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

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

PubMed

Bomblies, Arne

2014-07-03

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

Scenario-Based Spoken Interaction with Virtual Agents

ERIC Educational Resources Information Center

Morton, Hazel; Jack, Mervyn A.

2005-01-01

This paper describes a CALL approach which integrates software for speaker independent continuous speech recognition with embodied virtual agents and virtual worlds to create an immersive environment in which learners can converse in the target language in contextualised scenarios. The result is a self-access learning package: SPELL (Spoken…

Agent-based real-time signal coordination in congested networks.

DOT National Transportation Integrated Search

2014-01-01

This study is the continuation of a previous NEXTRANS study on agent-based reinforcement : learning methods for signal coordination in congested networks. In the previous study, the : formulation of a real-time agent-based traffic signal control in o...

The agent-based spatial information semantic grid

NASA Astrophysics Data System (ADS)

Cui, Wei; Zhu, YaQiong; Zhou, Yong; Li, Deren

2006-10-01

Analyzing the characteristic of multi-Agent and geographic Ontology, The concept of the Agent-based Spatial Information Semantic Grid (ASISG) is defined and the architecture of the ASISG is advanced. ASISG is composed with Multi-Agents and geographic Ontology. The Multi-Agent Systems are composed with User Agents, General Ontology Agent, Geo-Agents, Broker Agents, Resource Agents, Spatial Data Analysis Agents, Spatial Data Access Agents, Task Execution Agent and Monitor Agent. The architecture of ASISG have three layers, they are the fabric layer, the grid management layer and the application layer. The fabric layer what is composed with Data Access Agent, Resource Agent and Geo-Agent encapsulates the data of spatial information system so that exhibits a conceptual interface for the Grid management layer. The Grid management layer, which is composed with General Ontology Agent, Task Execution Agent and Monitor Agent and Data Analysis Agent, used a hybrid method to manage all resources that were registered in a General Ontology Agent that is described by a General Ontology System. The hybrid method is assembled by resource dissemination and resource discovery. The resource dissemination push resource from Local Ontology Agent to General Ontology Agent and the resource discovery pull resource from the General Ontology Agent to Local Ontology Agents. The Local Ontology Agent is derived from special domain and describes the semantic information of local GIS. The nature of the Local Ontology Agents can be filtrated to construct a virtual organization what could provides a global scheme. The virtual organization lightens the burdens of guests because they need not search information site by site manually. The application layer what is composed with User Agent, Geo-Agent and Task Execution Agent can apply a corresponding interface to a domain user. The functions that ASISG should provide are: 1) It integrates different spatial information systems on the semantic The Grid

A support vector machine approach to the automatic identification of fluorescence spectra emitted by biological agents

NASA Astrophysics Data System (ADS)

Gelfusa, M.; Murari, A.; Lungaroni, M.; Malizia, A.; Parracino, S.; Peluso, E.; Cenciarelli, O.; Carestia, M.; Pizzoferrato, R.; Vega, J.; Gaudio, P.

2016-10-01

Two of the major new concerns of modern societies are biosecurity and biosafety. Several biological agents (BAs) such as toxins, bacteria, viruses, fungi and parasites are able to cause damage to living systems either humans, animals or plants. Optical techniques, in particular LIght Detection And Ranging (LIDAR), based on the transmission of laser pulses and analysis of the return signals, can be successfully applied to monitoring the release of biological agents into the atmosphere. It is well known that most of biological agents tend to emit specific fluorescence spectra, which in principle allow their detection and identification, if excited by light of the appropriate wavelength. For these reasons, the detection of the UVLight Induced Fluorescence (UV-LIF) emitted by BAs is particularly promising. On the other hand, the stand-off detection of BAs poses a series of challenging issues; one of the most severe is the automatic discrimination between various agents which emit very similar fluorescence spectra. In this paper, a new data analysis method, based on a combination of advanced filtering techniques and Support Vector Machines, is described. The proposed approach covers all the aspects of the data analysis process, from filtering and denoising to automatic recognition of the agents. A systematic series of numerical tests has been performed to assess the potential and limits of the proposed methodology. The first investigations of experimental data have already given very encouraging results.

[Gadolinium-based contrast agents for magnetic resonance imaging].

PubMed

Carrasco Muñoz, S; Calles Blanco, C; Marcin, Javier; Fernández Álvarez, C; Lafuente Martínez, J

2014-06-01

Gadolinium-based contrast agents are increasingly being used in magnetic resonance imaging. These agents can improve the contrast in images and provide information about function and metabolism, increasing both sensitivity and specificity. We describe the gadolinium-based contrast agents that have been approved for clinical use, detailing their main characteristics based on their chemical structure, stability, and safety. In general terms, these compounds are safe. Nevertheless, adverse reactions, the possibility of nephrotoxicity from these compounds, and the possibility of developing nephrogenic systemic fibrosis will be covered in this article. Lastly, the article will discuss the current guidelines, recommendations, and contraindications for their clinical use, including the management of pregnant and breast-feeding patients. Copyright © 2014 SERAM. Published by Elsevier Espana. All rights reserved.

Extension Agents' Perceptions of a Blended Approach to Onboarding

ERIC Educational Resources Information Center

Harder, Amy; Zelaya, Priscilla; Roberts, T. Grady

2016-01-01

Extension organizations are challenged to provide onboarding to new employees that is comprehensive and high quality, yet cost-effective. The purpose of this study was to explore Extension agents' perceptions of participating in an onboarding program that used a blended approach involving face-to-face and online learning components. The objectives…

Comparison of an Agent-based Model of Disease Propagation with the Generalised SIR Epidemic Model

DTIC Science & Technology

2009-08-01

has become a practical method for conducting Epidemiological Modelling. In the agent- based approach the whole township can be modelled as a system of...SIR system was initially developed based on a very simplified model of social interaction. For instance an assumption of uniform population mixing was...simulating the progress of a disease within a host and of transmission between hosts is based upon Transportation Analysis and Simulation System

Fuselets: an agent based architecture for fusion of heterogeneous information and data

NASA Astrophysics Data System (ADS)

Beyerer, Jürgen; Heizmann, Michael; Sander, Jennifer

2006-04-01

A new architecture for fusing information and data from heterogeneous sources is proposed. The approach takes criminalistics as a model. In analogy to the work of detectives, who attempt to investigate crimes, software agents are initiated that pursue clues and try to consolidate or to dismiss hypotheses. Like their human pendants, they can, if questions beyond their competences arise, consult expert agents. Within the context of a certain task, region, and time interval, specialized operations are applied to each relevant information source, e.g. IMINT, SIGINT, ACINT,..., HUMINT, data bases etc. in order to establish hit lists of first clues. Each clue is described by its pertaining facts, uncertainties, and dependencies in form of a local degree-of-belief (DoB) distribution in a Bayesian sense. For each clue an agent is initiated which cooperates with other agents and experts. Expert agents support to make use of different information sources. Consultations of experts, capable to access certain information sources, result in changes of the DoB of the pertaining clue. According to the significance of concentration of their DoB distribution clues are abandoned or pursued further to formulate task specific hypotheses. Communications between the agents serve to find out whether different clues belong to the same cause and thus can be put together. At the end of the investigation process, the different hypotheses are evaluated by a jury and a final report is created that constitutes the fusion result. The approach proposed avoids calculating global DoB distributions by adopting a local Bayesian approximation and thus reduces the complexity of the exact problem essentially. Different information sources are transformed into DoB distributions using the maximum entropy paradigm and considering known facts as constraints. Nominal, ordinal and cardinal quantities can be treated within this framework equally. The architecture is scalable by tailoring the number of agents

A Sampling-Based Bayesian Approach for Cooperative Multiagent Online Search With Resource Constraints.

PubMed

Xiao, Hu; Cui, Rongxin; Xu, Demin

2018-06-01

This paper presents a cooperative multiagent search algorithm to solve the problem of searching for a target on a 2-D plane under multiple constraints. A Bayesian framework is used to update the local probability density functions (PDFs) of the target when the agents obtain observation information. To obtain the global PDF used for decision making, a sampling-based logarithmic opinion pool algorithm is proposed to fuse the local PDFs, and a particle sampling approach is used to represent the continuous PDF. Then the Gaussian mixture model (GMM) is applied to reconstitute the global PDF from the particles, and a weighted expectation maximization algorithm is presented to estimate the parameters of the GMM. Furthermore, we propose an optimization objective which aims to guide agents to find the target with less resource consumptions, and to keep the resource consumption of each agent balanced simultaneously. To this end, a utility function-based optimization problem is put forward, and it is solved by a gradient-based approach. Several contrastive simulations demonstrate that compared with other existing approaches, the proposed one uses less overall resources and shows a better performance of balancing the resource consumption.

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.

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

Protection of autonomous microgrids using agent-based distributed communication

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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

Agent-Based Modeling in Molecular Systems Biology.

PubMed

Soheilypour, Mohammad; Mofrad, Mohammad R K

2018-07-01

Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems at different spatiotemporal scales, there is still a need for methods that bridge the gap between spatially-detailed and computationally-efficient approaches. In this review, we summarize the capabilities of agent-based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease. © 2018 WILEY Periodicals, Inc.

Using an object-based grid system to evaluate a newly developed EP approach to formulate SVMs as applied to the classification of organophosphate nerve agents

NASA Astrophysics Data System (ADS)

Land, Walker H., Jr.; Lewis, Michael; Sadik, Omowunmi; Wong, Lut; Wanekaya, Adam; Gonzalez, Richard J.; Balan, Arun

2004-04-01

This paper extends the classification approaches described in reference [1] in the following way: (1.) developing and evaluating a new method for evolving organophosphate nerve agent Support Vector Machine (SVM) classifiers using Evolutionary Programming, (2.) conducting research experiments using a larger database of organophosphate nerve agents, and (3.) upgrading the architecture to an object-based grid system for evaluating the classification of EP derived SVMs. Due to the increased threats of chemical and biological weapons of mass destruction (WMD) by international terrorist organizations, a significant effort is underway to develop tools that can be used to detect and effectively combat biochemical warfare. This paper reports the integration of multi-array sensors with Support Vector Machines (SVMs) for the detection of organophosphates nerve agents using a grid computing system called Legion. Grid computing is the use of large collections of heterogeneous, distributed resources (including machines, databases, devices, and users) to support large-scale computations and wide-area data access. Finally, preliminary results using EP derived support vector machines designed to operate on distributed systems have provided accurate classification results. In addition, distributed training time architectures are 50 times faster when compared to standard iterative training time methods.

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

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.

Biocompatible blood pool MRI contrast agents based on hyaluronan

PubMed Central

Zhu, Wenlian; Artemov, Dmitri

2010-01-01

Biocompatible gadolinium blood pool contrast agents based on a biopolymer, hyaluronan, were investigated for magnetic resonance angiography application. Hyaluronan, a non-sulfated linear glucosaminoglycan composed of 2000–25,000 repeating disaccharide subunits of D-glucuronic acid and N-acetylglucosamine with molecular weight up to 20 MDa, is a major component of the extracellular matrix. Two gadolinium contrast agents based on 16 and 74 kDa hyaluronan were synthesized, both with R1 relaxivity around 5 mM−1 s−1 per gadolinium at 9.4 T at 25°C. These two hyaluronan based agents show significant enhancement of the vasculature for an extended period of time. Initial excretion was primarily through the renal system. Later uptake was observed in the stomach and lower gastrointestinal tract. Macromolecular hyaluronan-based gadolinium agents have a high clinical translation potential as hyaluronan is already approved by FDA for a variety of medical applications. PMID:21504061

A Comparative Study of Probability Collectives Based Multi-agent Systems and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Huang, Chien-Feng; Wolpert, David H.; Bieniawski, Stefan; Strauss, Charles E. M.

2005-01-01

We compare Genetic Algorithms (GA's) with Probability Collectives (PC), a new framework for distributed optimization and control. In contrast to GA's, PC-based methods do not update populations of solutions. Instead they update an explicitly parameterized probability distribution p over the space of solutions. That updating of p arises as the optimization of a functional of p. The functional is chosen so that any p that optimizes it should be p peaked about good solutions. The PC approach works in both continuous and discrete problems. It does not suffer from the resolution limitation of the finite bit length encoding of parameters into GA alleles. It also has deep connections with both game theory and statistical physics. We review the PC approach using its motivation as the information theoretic formulation of bounded rationality for multi-agent systems. It is then compared with GA's on a diverse set of problems. To handle high dimensional surfaces, in the PC method investigated here p is restricted to a product distribution. Each distribution in that product is controlled by a separate agent. The test functions were selected for their difficulty using either traditional gradient descent or genetic algorithms. On those functions the PC-based approach significantly outperforms traditional GA's in both rate of descent, trapping in false minima, and long term optimization.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gallo, Giulia

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.more » 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.« less

Nanotechnology based approaches for anti-diabetic drugs delivery.

PubMed

Kesharwani, Prashant; Gorain, Bapi; Low, Siew Yeng; Tan, Siew Ann; Ling, Emily Chai Siaw; Lim, Yin Khai; Chin, Chuan Ming; Lee, Pei Yee; Lee, Chun Mey; Ooi, Chun Haw; Choudhury, Hira; Pandey, Manisha

2018-02-01

Nanotechnology science has been diverged its application in several fields with the advantages to operate with nanometric range of objects. Emerging field of nanotechnology has been also being approached and applied in medical biology for improved efficacy and safety. Increased success in therapeutic field has focused several approaches in the treatment of the common metabolic disorder, diabetes. The development of nanocarriers for improved delivery of different oral hypoglycemic agents compared to conventional therapies includes nanoparticles (NPs), liposomes, dendrimer, niosomes and micelles, which produces great control over the increased blood glucose level and thus becoming an eye catching and most promising technology now-a-days. Besides, embellishment of nanocarriers with several ligands makes it more targeted delivery with the protection of entrapped hypoglycaemic agents against degradation, thereby optimizing prolonged blood glucose lowering effect. Thus, nanocarriers of hypoglycemic agents provide the aim towards improved diabetes management with minimized risk of acute and chronic complications. In this review, we provide an overview on distinctive features of each nano-based drug delivery system for diabetic treatment and current NPs applications in diabetes management. Copyright © 2017 Elsevier B.V. All rights reserved.

Designing Agent Utilities for Coordinated, Scalable and Robust Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Tumer, Kagan

2005-01-01

Coordinating the behavior of a large number of agents to achieve a system level goal poses unique design challenges. In particular, problems of scaling (number of agents in the thousands to tens of thousands), observability (agents have limited sensing capabilities), and robustness (the agents are unreliable) make it impossible to simply apply methods developed for small multi-agent systems composed of reliable agents. To address these problems, we present an approach based on deriving agent goals that are aligned with the overall system goal, and can be computed using information readily available to the agents. Then, each agent uses a simple reinforcement learning algorithm to pursue its own goals. Because of the way in which those goals are derived, there is no need to use difficult to scale external mechanisms to force collaboration or coordination among the agents, or to ensure that agents actively attempt to appropriate the tasks of agents that suffered failures. To present these results in a concrete setting, we focus on the problem of finding the sub-set of a set of imperfect devices that results in the best aggregate device. This is a large distributed agent coordination problem where each agent (e.g., device) needs to determine whether to be part of the aggregate device. Our results show that the approach proposed in this work provides improvements of over an order of magnitude over both traditional search methods and traditional multi-agent methods. Furthermore, the results show that even in extreme cases of agent failures (i.e., half the agents failed midway through the simulation) the system's performance degrades gracefully and still outperforms a failure-free and centralized search algorithm. The results also show that the gains increase as the size of the system (e.g., number of agents) increases. This latter result is particularly encouraging and suggests that this method is ideally suited for domains where the number of agents is currently in the

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.

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

DTIC Science & Technology

2012-01-01

different parts of the human body to cure diseases such as hypertension, cancer, or heart disease. And we need to control microbes for the efficient...antelope herd interacts with an aggregated prey agent such as cheetahs or lions, the size of each may expand or contract accordingly). Of course, such

A multi-agent approach to intelligent monitoring in smart grids

NASA Astrophysics Data System (ADS)

Vallejo, D.; Albusac, J.; Glez-Morcillo, C.; Castro-Schez, J. J.; Jiménez, L.

2014-04-01

In this paper, we propose a scalable multi-agent architecture to give support to smart grids, paying special attention to the intelligent monitoring of distribution substations. The data gathered by multiple sensors are used by software agents that are responsible for monitoring different aspects or events of interest, such as normal voltage values or unbalanced intensity values that can end up blowing fuses and decreasing the quality of service of end consumers. The knowledge bases of these agents have been built by means of a formal model for normality analysis that has been successfully used in other surveillance domains. The architecture facilitates the integration of new agents and can be easily configured and deployed to monitor different environments. The experiments have been conducted over a power distribution network.

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.

Construction and Evaluation of Animated Teachable Agents

ERIC Educational Resources Information Center

Bodenheimer, Bobby; Williams, Betsy; Kramer, Mattie Ruth; Viswanath, Karun; Balachandran, Ramya; Belynne, Kadira; Biswas, Gautam

2009-01-01

This article describes the design decisions, technical approach, and evaluation of the animation and interface components for an agent-based system that allows learners to learn by teaching. Students learn by teaching an animated agent using a visual representation. The agent can answer questions about what she has been taught and take quizzes.…

Spherical Nucleic Acids as Intracellular Agents for Nucleic Acid Based Therapeutics

NASA Astrophysics Data System (ADS)

Hao, Liangliang

Recent functional discoveries on the noncoding sequences of human genome and transcriptome could lead to revolutionary treatment modalities because the noncoding RNAs (ncRNAs) can be applied as therapeutic agents to manipulate disease-causing genes. To date few nucleic acid-based therapeutics have been translated into the clinic due to challenges in the delivery of the oligonucleotide agents in an effective, cell specific, and non-toxic fashion. Unmodified oligonucleotide agents are destroyed rapidly in biological fluids by enzymatic degradation and have difficulty crossing the plasma membrane without the aid of transfection reagents, which often cause inflammatory, cytotoxic, or immunogenic side effects. Spherical nucleic acids (SNAs), nanoparticles consisting of densely organized and highly oriented oligonucleotides, pose one possible solution to circumventing these problems in both the antisense and RNA interference (RNAi) pathways. The unique three dimensional architecture of SNAs protects the bioactive oligonucleotides from unspecific degradation during delivery and supports their targeting of class A scavenger receptors and endocytosis via a lipid-raft-dependent, caveolae-mediated pathway. Owing to their unique structure, SNAs are able to cross cell membranes and regulate target genes expression as a single entity, without triggering the cellular innate immune response. Herein, my thesis has focused on understanding the interactions between SNAs and cellular components and developing SNA-based nanostructures to improve therapeutic capabilities. Specifically, I developed a novel SNA-based, nanoscale agent for delivery of therapeutic oligonucleotides to manipulate microRNAs (miRNAs), the endogenous post-transcriptional gene regulators. I investigated the role of SNAs involving miRNAs in anti-cancer or anti-inflammation responses in cells and in in vivo murine disease models via systemic injection. Furthermore, I explored using different strategies to construct

Mathematical modeling of malaria infection with innate and adaptive immunity in individuals and agent-based communities.

PubMed

Gurarie, David; Karl, Stephan; Zimmerman, Peter A; King, Charles H; St Pierre, Timothy G; Davis, Timothy M E

2012-01-01

Agent-based modeling of Plasmodium falciparum infection offers an attractive alternative to the conventional Ross-Macdonald methodology, as it allows simulation of heterogeneous communities subjected to realistic transmission (inoculation patterns). We developed a new, agent based model that accounts for the essential in-host processes: parasite replication and its regulation by innate and adaptive immunity. The model also incorporates a simplified version of antigenic variation by Plasmodium falciparum. We calibrated the model using data from malaria-therapy (MT) studies, and developed a novel calibration procedure that accounts for a deterministic and a pseudo-random component in the observed parasite density patterns. Using the parasite density patterns of 122 MT patients, we generated a large number of calibrated parameters. The resulting data set served as a basis for constructing and simulating heterogeneous agent-based (AB) communities of MT-like hosts. We conducted several numerical experiments subjecting AB communities to realistic inoculation patterns reported from previous field studies, and compared the model output to the observed malaria prevalence in the field. There was overall consistency, supporting the potential of this agent-based methodology to represent transmission in realistic communities. Our approach represents a novel, convenient and versatile method to model Plasmodium falciparum infection.

Enhanced Deployment Strategy for Role-based Hierarchical Application Agents in Wireless Sensor Networks with Established Clusterheads

NASA Astrophysics Data System (ADS)

Gendreau, Audrey

Efficient self-organizing virtual clusterheads that supervise data collection based on their wireless connectivity, risk, and overhead costs, are an important element of Wireless Sensor Networks (WSNs). This function is especially critical during deployment when system resources are allocated to a subsequent application. In the presented research, a model used to deploy intrusion detection capability on a Local Area Network (LAN), in the literature, was extended to develop a role-based hierarchical agent deployment algorithm for a WSN. The resulting model took into consideration the monitoring capability, risk, deployment distribution cost, and monitoring cost associated with each node. Changing the original LAN methodology approach to model a cluster-based sensor network depended on the ability to duplicate a specific parameter that represented the monitoring capability. Furthermore, other parameters derived from a LAN can elevate costs and risk of deployment, as well as jeopardize the success of an application on a WSN. A key component of the approach presented in this research was to reduce the costs when established clusterheads in the network were found to be capable of hosting additional detection agents. In addition, another cost savings component of the study addressed the reduction of vulnerabilities associated with deployment of agents to high volume nodes. The effectiveness of the presented method was validated by comparing it against a type of a power-based scheme that used each node's remaining energy as the deployment value. While available energy is directly related to the model used in the presented method, the study deliberately sought out nodes that were identified with having superior monitoring capability, cost less to create and sustain, and are at low-risk of an attack. This work investigated improving the efficiency of an intrusion detection system (IDS) by using the proposed model to deploy monitoring agents after a temperature sensing

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.

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.

Antibody-Based Agents in the Management of Antibiotic-Resistant Staphylococcus aureus Diseases

PubMed Central

Speziale, Pietro; Rindi, Simonetta

2018-01-01

Staphylococcus aureus is a human pathogen that can cause a wide spectrum of diseases, including sepsis, pneumonia, arthritis, and endocarditis. Ineffective treatment of a number of staphylococcal infections with antibiotics is due to the development and spread of antibiotic-resistant strains following decades of antibiotic usage. This has generated renewed interest within the scientific community in alternative therapeutic agents, such as anti-S. aureus antibodies. Although the role of antibodies in the management of S. aureus diseases is controversial, the success of this pathogen in neutralizing humoral immunity clearly indicates that antibodies offer the host extensive protection. In this review, we report an update on efforts to develop antibody-based agents, particularly monoclonal antibodies, and their therapeutic potential in the passive immunization approach to the treatment and prevention of S. aureus infections. PMID:29533985

An immunity-based anomaly detection system with sensor agents.

PubMed

Okamoto, Takeshi; Ishida, Yoshiteru

2009-01-01

This paper proposes an immunity-based anomaly detection system with sensor agents based on the specificity and diversity of the immune system. Each agent is specialized to react to the behavior of a specific user. Multiple diverse agents decide whether the behavior is normal or abnormal. Conventional systems have used only a single sensor to detect anomalies, while the immunity-based system makes use of multiple sensors, which leads to improvements in detection accuracy. In addition, we propose an evaluation framework for the anomaly detection system, which is capable of evaluating the differences in detection accuracy between internal and external anomalies. This paper focuses on anomaly detection in user's command sequences on UNIX-like systems. In experiments, the immunity-based system outperformed some of the best conventional systems.

An Agent-Based Data Mining System for Ontology Evolution

NASA Astrophysics Data System (ADS)

Hadzic, Maja; Dillon, Darshan

We have developed an evidence-based mental health ontological model that represents mental health in multiple dimensions. The ongoing addition of new mental health knowledge requires a continual update of the Mental Health Ontology. In this paper, we describe how the ontology evolution can be realized using a multi-agent system in combination with data mining algorithms. We use the TICSA methodology to design this multi-agent system which is composed of four different types of agents: Information agent, Data Warehouse agent, Data Mining agents and Ontology agent. We use UML 2.1 sequence diagrams to model the collaborative nature of the agents and a UML 2.1 composite structure diagram to model the structure of individual agents. The Mental Heath Ontology has the potential to underpin various mental health research experiments of a collaborative nature which are greatly needed in times of increasing mental distress and illness.

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.

Knowledge Ecology for Conceptual Growth: Teachers as Active Agents in Developing a Pluriliteracies Approach to Teaching for Learning (PTL)

ERIC Educational Resources Information Center

Coyle, Do; Halbach, Ana; Meyer, Oliver; Schuck, Kevin

2018-01-01

This article explores how a group of educators and researchers enacted an inclusive process of conceptual growth involving teachers and teacher educators as active agents, knowledge builders and meaning-makers in the development of a Pluriliteracies approach to Teaching for Learning (PTL). The evolution of a working model based on five emergent…

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

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

Towards an agent-oriented programming language based on Scala

NASA Astrophysics Data System (ADS)

Mitrović, Dejan; Ivanović, Mirjana; Budimac, Zoran

2012-09-01

Scala and its multi-threaded model based on actors represent an excellent framework for developing purely reactive agents. This paper presents an early research on extending Scala with declarative programming constructs, which would result in a new agent-oriented programming language suitable for developing more advanced, BDI agent architectures. The main advantage the new language over many other existing solutions for programming BDI agents is a natural and straightforward integration of imperative and declarative programming constructs, fitted under a single development framework.

The Study on Collaborative Manufacturing Platform Based on Agent

NASA Astrophysics Data System (ADS)

Zhang, Xiao-yan; Qu, Zheng-geng

To fulfill the trends of knowledge-intensive in collaborative manufacturing development, we have described multi agent architecture supporting knowledge-based platform of collaborative manufacturing development platform. In virtue of wrapper service and communication capacity agents provided, the proposed architecture facilitates organization and collaboration of multi-disciplinary individuals and tools. By effectively supporting the formal representation, capture, retrieval and reuse of manufacturing knowledge, the generalized knowledge repository based on ontology library enable engineers to meaningfully exchange information and pass knowledge across boundaries. Intelligent agent technology increases traditional KBE systems efficiency and interoperability and provides comprehensive design environments for engineers.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Haifeng; Vorobeychik, Yevgeniy; Letchford, Joshua

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

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

iMuseumA: An Agent-Based Context-Aware Intelligent Museum System

PubMed Central

Ayala, Inmaculada; Amor, Mercedes; Pinto, Mónica; Fuentes, Lidia; Gámez, Nadia

2014-01-01

Currently, museums provide their visitors with interactive tour guide applications that can be installed in mobile devices and provide timely tailor-made multimedia information about exhibits on display. In this paper, we argue that mobile devices not only could provide help to visitors, but also to museum staff. Our goal is to integrate, within the same system, multimedia tour guides with the management facilities required by museums. In this paper, we present iMuseumA (intelligent museum with agents), a mobile-based solution to customize visits and perform context-aware management tasks. iMuseumA follows an agent-based approach, which makes it possible to interact easily with the museum environment and make decisions based on its current status. This system is currently deployed in the Museum of Informatics at the Informatics School of the University of Málaga, and its main contributions are: (i) a mobile application that provides management facilities to museum staff by means of sensing and processing environmental data; (ii) providing an integrated solution for visitors, tour guides and museum staff that allows coordination and communication enrichment among different groups of users; (iii) using and benefiting from group communication for heterogeneous groups of users that can be created on demand. PMID:25390409

iMuseumA: an agent-based context-aware intelligent museum system.

PubMed

Ayala, Inmaculada; Amor, Mercedes; Pinto, Mónica; Fuentes, Lidia; Gámez, Nadia

2014-11-10

Currently, museums provide their visitors with interactive tour guide applications that can be installed in mobile devices and provide timely tailor-made multimedia information about exhibits on display. In this paper, we argue that mobile devices not only could provide help to visitors, but also to museum staff. Our goal is to integrate, within the same system, multimedia tour guides with the management facilities required by museums. In this paper, we present iMuseumA (intelligent museum with agents), a mobile-based solution to customize visits and perform context-aware management tasks. iMuseumA follows an agent-based approach, which makes it possible to interact easily with the museum environment and make decisions based on its current status. This system is currently deployed in the Museum of Informatics at the Informatics School of the University of Málaga, and its main contributions are: (i) a mobile application that provides management facilities to museum staff by means of sensing and processing environmental data; (ii) providing an integrated solution for visitors, tour guides and museum staff that allows coordination and communication enrichment among different groups of users; (iii) using and benefiting from group communication for heterogeneous groups of users that can be created on demand.

A knowledge base architecture for distributed knowledge agents

NASA Technical Reports Server (NTRS)

Riedesel, Joel; Walls, Bryan

1990-01-01

A tuple space based object oriented model for knowledge base representation and interpretation is presented. An architecture for managing distributed knowledge agents is then implemented within the model. The general model is based upon a database implementation of a tuple space. Objects are then defined as an additional layer upon the database. The tuple space may or may not be distributed depending upon the database implementation. A language for representing knowledge and inference strategy is defined whose implementation takes advantage of the tuple space. The general model may then be instantiated in many different forms, each of which may be a distinct knowledge agent. Knowledge agents may communicate using tuple space mechanisms as in the LINDA model as well as using more well known message passing mechanisms. An implementation of the model is presented describing strategies used to keep inference tractable without giving up expressivity. An example applied to a power management and distribution network for Space Station Freedom is given.

Can longitudinal generalized estimating equation models distinguish network influence and homophily? An agent-based modeling approach to measurement characteristics.

PubMed

Sauser Zachrison, Kori; Iwashyna, Theodore J; Gebremariam, Achamyeleh; Hutchins, Meghan; Lee, Joyce M

2016-12-28

Connected individuals (or nodes) in a network are more likely to be similar than two randomly selected nodes due to homophily and/or network influence. Distinguishing between these two influences is an important goal in network analysis, and generalized estimating equation (GEE) analyses of longitudinal dyadic network data are an attractive approach. It is not known to what extent such regressions can accurately extract underlying data generating processes. Therefore our primary objective is to determine to what extent, and under what conditions, does the GEE-approach recreate the actual dynamics in an agent-based model. We generated simulated cohorts with pre-specified network characteristics and attachments in both static and dynamic networks, and we varied the presence of homophily and network influence. We then used statistical regression and examined the GEE model performance in each cohort to determine whether the model was able to detect the presence of homophily and network influence. In cohorts with both static and dynamic networks, we find that the GEE models have excellent sensitivity and reasonable specificity for determining the presence or absence of network influence, but little ability to distinguish whether or not homophily is present. The GEE models are a valuable tool to examine for the presence of network influence in longitudinal data, but are quite limited with respect to homophily.

Applications of agent-based modeling to nutrient movement Lake Michigan

EPA Science Inventory

As part of an ongoing project aiming to provide useful information for nearshore management (harmful algal blooms, nutrient loading), we explore the value of agent-based models in Lake Michigan. Agent-based models follow many individual “agents” moving through a simul...

Laser-Based Trespassing Prediction in Restrictive Environments: A Linear Approach

PubMed Central

Cheein, Fernando Auat; Scaglia, Gustavo

2012-01-01

Stationary range laser sensors for intruder monitoring, restricted space violation detections and workspace determination are extensively used in risky environments. In this work we present a linear based approach for predicting the presence of moving agents before they trespass a laser-based restricted space. Our approach is based on the Taylor's series expansion of the detected objects' movements. The latter makes our proposal suitable for embedded applications. In the experimental results (carried out in different scenarios) presented herein, our proposal shows 100% of effectiveness in predicting trespassing situations. Several implementation results and statistics analysis showing the performance of our proposal are included in this work.

SiC: An Agent Based Architecture for Preventing and Detecting Attacks to Ubiquitous Databases

NASA Astrophysics Data System (ADS)

Pinzón, Cristian; de Paz, Yanira; Bajo, Javier; Abraham, Ajith; Corchado, Juan M.

One of the main attacks to ubiquitous databases is the structure query language (SQL) injection attack, which causes severe damages both in the commercial aspect and in the user’s confidence. This chapter proposes the SiC architecture as a solution to the SQL injection attack problem. This is a hierarchical distributed multiagent architecture, which involves an entirely new approach with respect to existing architectures for the prevention and detection of SQL injections. SiC incorporates a kind of intelligent agent, which integrates a case-based reasoning system. This agent, which is the core of the architecture, allows the application of detection techniques based on anomalies as well as those based on patterns, providing a great degree of autonomy, flexibility, robustness and dynamic scalability. The characteristics of the multiagent system allow an architecture to detect attacks from different types of devices, regardless of the physical location. The architecture has been tested on a medical database, guaranteeing safe access from various devices such as PDAs and notebook computers.

Emergence of Swarming Behavior: Foraging Agents Evolve Collective Motion Based on Signaling.

PubMed

Witkowski, Olaf; Ikegami, Takashi

2016-01-01

Swarming behavior is common in biology, from cell colonies to insect swarms and bird flocks. However, the conditions leading to the emergence of such behavior are still subject to research. Since Reynolds' boids, many artificial models have reproduced swarming behavior, focusing on details ranging from obstacle avoidance to the introduction of fixed leaders. This paper presents a model of evolved artificial agents, able to develop swarming using only their ability to listen to each other's signals. The model simulates a population of agents looking for a vital resource they cannot directly detect, in a 3D environment. Instead of a centralized algorithm, each agent is controlled by an artificial neural network, whose weights are encoded in a genotype and adapted by an original asynchronous genetic algorithm. The results demonstrate that agents progressively evolve the ability to use the information exchanged between each other via signaling to establish temporary leader-follower relations. These relations allow agents to form swarming patterns, emerging as a transient behavior that improves the agents' ability to forage for the resource. Once they have acquired the ability to swarm, the individuals are able to outperform the non-swarmers at finding the resource. The population hence reaches a neutral evolutionary space which leads to a genetic drift of the genotypes. This reductionist approach to signal-based swarming not only contributes to shed light on the minimal conditions for the evolution of a swarming behavior, but also more generally it exemplifies the effect communication can have on optimal search patterns in collective groups of individuals.

Multi-objective optimization of radiotherapy: distributed Q-learning and agent-based simulation

NASA Astrophysics Data System (ADS)

Jalalimanesh, Ammar; Haghighi, Hamidreza Shahabi; Ahmadi, Abbas; Hejazian, Hossein; Soltani, Madjid

2017-09-01

Radiotherapy (RT) is among the regular techniques for the treatment of cancerous tumours. Many of cancer patients are treated by this manner. Treatment planning is the most important phase in RT and it plays a key role in therapy quality achievement. As the goal of RT is to irradiate the tumour with adequately high levels of radiation while sparing neighbouring healthy tissues as much as possible, it is a multi-objective problem naturally. In this study, we propose an agent-based model of vascular tumour growth and also effects of RT. Next, we use multi-objective distributed Q-learning algorithm to find Pareto-optimal solutions for calculating RT dynamic dose. We consider multiple objectives and each group of optimizer agents attempt to optimise one of them, iteratively. At the end of each iteration, agents compromise the solutions to shape the Pareto-front of multi-objective problem. We propose a new approach by defining three schemes of treatment planning created based on different combinations of our objectives namely invasive, conservative and moderate. In invasive scheme, we enforce killing cancer cells and pay less attention about irradiation effects on normal cells. In conservative scheme, we take more care of normal cells and try to destroy cancer cells in a less stressed manner. The moderate scheme stands in between. For implementation, each of these schemes is handled by one agent in MDQ-learning algorithm and the Pareto optimal solutions are discovered by the collaboration of agents. By applying this methodology, we could reach Pareto treatment plans through building different scenarios of tumour growth and RT. The proposed multi-objective optimisation algorithm generates robust solutions and finds the best treatment plan for different conditions.

Cooperative vehicles for robust traffic congestion reduction: An analysis based on algorithmic, environmental and agent behavioral factors

PubMed Central

Desai, Prajakta; Desai, Aniruddha

2017-01-01

Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN), wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction), across variations in: (a) environmental parameters such as road network topology and configuration; (b) algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c) agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies. PMID:28792513

Cooperative vehicles for robust traffic congestion reduction: An analysis based on algorithmic, environmental and agent behavioral factors.

PubMed

Desai, Prajakta; Loke, Seng W; Desai, Aniruddha

2017-01-01

Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN), wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction), across variations in: (a) environmental parameters such as road network topology and configuration; (b) algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c) agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies.

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

DTIC Science & Technology

2012-09-30

System N Agent « datatype » SoS Architecture -Receives Capabilities1 -Provides Capabilities1 1 -Provides Capabilities1 1 -Provides Capabilities1 -Updates 1...fitness, or objective function. The structure of the SoS Agent is depicted in Figure 10. SoS Agent Architecture « datatype » Initial SoS...Architecture «subsystem» Fuzzy Inference Engine FAM « datatype » Affordability « datatype » Flexibility « datatype » Performance « datatype » Robustness Input Input

Agents in bioinformatics, computational and systems biology.

PubMed

Merelli, Emanuela; Armano, Giuliano; Cannata, Nicola; Corradini, Flavio; d'Inverno, Mark; Doms, Andreas; Lord, Phillip; Martin, Andrew; Milanesi, Luciano; Möller, Steffen; Schroeder, Michael; Luck, Michael

2007-01-01

The adoption of agent technologies and multi-agent systems constitutes an emerging area in bioinformatics. In this article, we report on the activity of the Working Group on Agents in Bioinformatics (BIOAGENTS) founded during the first AgentLink III Technical Forum meeting on the 2nd of July, 2004, in Rome. The meeting provided an opportunity for seeding collaborations between the agent and bioinformatics communities to develop a different (agent-based) approach of computational frameworks both for data analysis and management in bioinformatics and for systems modelling and simulation in computational and systems biology. The collaborations gave rise to applications and integrated tools that we summarize and discuss in context of the state of the art in this area. We investigate on future challenges and argue that the field should still be explored from many perspectives ranging from bio-conceptual languages for agent-based simulation, to the definition of bio-ontology-based declarative languages to be used by information agents, and to the adoption of agents for computational grids.

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

An Approach to Quantify Workload in a System of Agents

NASA Technical Reports Server (NTRS)

Stocker, Richard; Rungta, Neha; Mercer, Eric; Raimondi, Franco; Holbrook, Jon; Cardoza, Colleen; Goodrich, Michael

2015-01-01

The role of humans in aviation and other domains continues to shift from manual control to automation monitoring. Studies have found that humans are often poorly suited for monitoring roles, and workload can easily spike in off-nominal situations. Current workload measurement tools, like NASA TLX, use human operators to assess their own workload after using a prototype system. Such measures are used late in the design process and can result in ex- pensive alterations when problems are discovered. Our goal in this work is to provide a quantitative workload measure for use early in the design process. We leverage research in human cognition to de ne metrics that can measure workload on belief-desire-intentions based multi-agent systems. These measures can alert designers to potential workload issues early in design. We demonstrate the utility of our approach by characterizing quantitative differences in the workload for a single pilot operations model compared to a traditional two pilot model.

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.

Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology

NASA Astrophysics Data System (ADS)

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

2005-11-01

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.

Agent-based method for distributed clustering of textual information

DOEpatents

Potok, Thomas E [Oak Ridge, TN; Reed, Joel W [Knoxville, TN; Elmore, Mark T [Oak Ridge, TN; Treadwell, Jim N [Louisville, TN

2010-09-28

A computer method and system for storing, retrieving and displaying information has a multiplexing agent (20) that calculates a new document vector (25) for a new document (21) to be added to the system and transmits the new document vector (25) to master cluster agents (22) and cluster agents (23) for evaluation. These agents (22, 23) perform the evaluation and return values upstream to the multiplexing agent (20) based on the similarity of the document to documents stored under their control. The multiplexing agent (20) then sends the document (21) and the document vector (25) to the master cluster agent (22), which then forwards it to a cluster agent (23) or creates a new cluster agent (23) to manage the document (21). The system also searches for stored documents according to a search query having at least one term and identifying the documents found in the search, and displays the documents in a clustering display (80) of similarity so as to indicate similarity of the documents to each other.

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

PubMed

Kittipittayakorn, Cholada; Ying, Kuo-Ching

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.

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

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.

Systems approach to investigating host-pathogen interactions in infections with the biothreat agent Francisella. Constraints-based model of Francisella tularensis

PubMed Central

2010-01-01

Background Francisella tularensis is a prototypic example of a pathogen for which few experimental datasets exist, but for which copious high-throughout data are becoming available because of its re-emerging significance as biothreat agent. The virulence of Francisella tularensis depends on its growth capabilities within a defined environmental niche of the host cell. Results We reconstructed the metabolism of Francisella as a stoichiometric matrix. This systems biology approach demonstrated that changes in carbohydrate utilization and amino acid metabolism play a pivotal role in growth, acid resistance, and energy homeostasis during infection with Francisella. We also show how varying the expression of certain metabolic genes in different environments efficiently controls the metabolic capacity of F. tularensis. Selective gene-expression analysis showed modulation of sugar catabolism by switching from oxidative metabolism (TCA cycle) in the initial stages of infection to fatty acid oxidation and gluconeogenesis later on. Computational analysis with constraints derived from experimental data revealed a limited set of metabolic genes that are operational during infection. Conclusions This integrated systems approach provides an important tool to understand the pathogenesis of an ill-characterized biothreat agent and to identify potential novel drug targets when rapid target identification is required should such microbes be intentionally released or become epidemic. PMID:20731870

Towards a framework for agent-based image analysis of remote-sensing data.

PubMed

Hofmann, Peter; Lettmayer, Paul; Blaschke, Thomas; Belgiu, Mariana; Wegenkittl, Stefan; Graf, Roland; Lampoltshammer, Thomas Josef; Andrejchenko, Vera

2015-04-03

Object-based image analysis (OBIA) as a paradigm for analysing remotely sensed image data has in many cases led to spatially and thematically improved classification results in comparison to pixel-based approaches. Nevertheless, robust and transferable object-based solutions for automated image analysis capable of analysing sets of images or even large image archives without any human interaction are still rare. A major reason for this lack of robustness and transferability is the high complexity of image contents: Especially in very high resolution (VHR) remote-sensing data with varying imaging conditions or sensor characteristics, the variability of the objects' properties in these varying images is hardly predictable. The work described in this article builds on so-called rule sets. While earlier work has demonstrated that OBIA rule sets bear a high potential of transferability, they need to be adapted manually, or classification results need to be adjusted manually in a post-processing step. In order to automate these adaptation and adjustment procedures, we investigate the coupling, extension and integration of OBIA with the agent-based paradigm, which is exhaustively investigated in software engineering. The aims of such integration are (a) autonomously adapting rule sets and (b) image objects that can adopt and adjust themselves according to different imaging conditions and sensor characteristics. This article focuses on self-adapting image objects and therefore introduces a framework for agent-based image analysis (ABIA).

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.

An Agent-based Modeling of Water-Food Nexus towards Sustainable Management of Urban Water Resources

NASA Astrophysics Data System (ADS)

Esmaeili, N.; Kanta, L.

2017-12-01

Growing population, urbanization, and climate change have put tremendous stress on water systems in many regions. A shortage in water system not only affects water users of a municipality but also that of food system. About 70% of global water is withdrawn for agriculture; livestock and dairy productions are also dependent on water availability. Although researchers and policy makers have identified and emphasized the water-food (WF) nexus in recent decade, most existing WF models offer strategies to reduce trade-offs and to generate benefits without considering feedback loops and adaptations between those systems. Feedback loops between water and food system can help understand long-term behavioral trends between water users of the integrated WF system which, in turn, can help manage water resources sustainably. An Agent-based modeling approach is applied here to develop a conceptual framework of WF systems. All water users in this system are modeled as agents, who are capable of making decisions and can adapt new behavior based on inputs from other agents in a shared environment through a set of logical and mathematical rules. Residential and commercial/industrial consumers are represented as municipal agents; crop, livestock, and dairy farmers are represented as food agents; and water management officials are represented as policy agent. During the period of water shortage, policy agent will propose/impose various water conservation measures, such as adapting water-efficient technologies, banning outdoor irrigation, implementing supplemental irrigation, using recycled water for livestock/dairy production, among others. Municipal and food agents may adapt conservation strategies and will update their demand accordingly. Emergent properties of the WF nexus will arise through dynamic interactions between various actors of water and food system. This model will be implemented to a case study for resource allocation and future policy development.

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

Research on Production Scheduling System with Bottleneck Based on Multi-agent

NASA Astrophysics Data System (ADS)

Zhenqiang, Bao; Weiye, Wang; Peng, Wang; Pan, Quanke

Aimed at the imbalance problem of resource capacity in Production Scheduling System, this paper uses Production Scheduling System based on multi-agent which has been constructed, and combines the dynamic and autonomous of Agent; the bottleneck problem in the scheduling is solved dynamically. Firstly, this paper uses Bottleneck Resource Agent to find out the bottleneck resource in the production line, analyses the inherent mechanism of bottleneck, and describes the production scheduling process based on bottleneck resource. Bottleneck Decomposition Agent harmonizes the relationship of job's arrival time and transfer time in Bottleneck Resource Agent and Non-Bottleneck Resource Agents, therefore, the dynamic scheduling problem is simplified as the single machine scheduling of each resource which takes part in the scheduling. Finally, the dynamic real-time scheduling problem is effectively solved in Production Scheduling System.

Chronic Heart Failure Follow-up Management Based on Agent Technology.

PubMed

Mohammadzadeh, Niloofar; Safdari, Reza

2015-10-01

Monitoring heart failure patients through continues assessment of sign and symptoms by information technology tools lead to large reduction in re-hospitalization. Agent technology is one of the strongest artificial intelligence areas; therefore, it can be expected to facilitate, accelerate, and improve health services especially in home care and telemedicine. The aim of this article is to provide an agent-based model for chronic heart failure (CHF) follow-up management. This research was performed in 2013-2014 to determine appropriate scenarios and the data required to monitor and follow-up CHF patients, and then an agent-based model was designed. Agents in the proposed model perform the following tasks: medical data access, communication with other agents of the framework and intelligent data analysis, including medical data processing, reasoning, negotiation for decision-making, and learning capabilities. The proposed multi-agent system has ability to learn and thus improve itself. Implementation of this model with more and various interval times at a broader level could achieve better results. The proposed multi-agent system is no substitute for cardiologists, but it could assist them in decision-making.

Chronic Heart Failure Follow-up Management Based on Agent Technology

PubMed Central

Safdari, Reza

2015-01-01

Objectives Monitoring heart failure patients through continues assessment of sign and symptoms by information technology tools lead to large reduction in re-hospitalization. Agent technology is one of the strongest artificial intelligence areas; therefore, it can be expected to facilitate, accelerate, and improve health services especially in home care and telemedicine. The aim of this article is to provide an agent-based model for chronic heart failure (CHF) follow-up management. Methods This research was performed in 2013-2014 to determine appropriate scenarios and the data required to monitor and follow-up CHF patients, and then an agent-based model was designed. Results Agents in the proposed model perform the following tasks: medical data access, communication with other agents of the framework and intelligent data analysis, including medical data processing, reasoning, negotiation for decision-making, and learning capabilities. Conclusions The proposed multi-agent system has ability to learn and thus improve itself. Implementation of this model with more and various interval times at a broader level could achieve better results. The proposed multi-agent system is no substitute for cardiologists, but it could assist them in decision-making. PMID:26618038

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

2017-10-01

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. © 2016 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

The Impacts of Information-Sharing Mechanisms on Spatial Market Formation Based on Agent-Based Modeling

PubMed Central

Li, Qianqian; Yang, Tao; Zhao, Erbo; Xia, Xing’ang; Han, Zhangang

2013-01-01

There has been an increasing interest in the geographic aspects of economic development, exemplified by P. Krugman’s logical analysis. We show in this paper that the geographic aspects of economic development can be modeled using multi-agent systems that incorporate multiple underlying factors. The extent of information sharing is assumed to be a driving force that leads to economic geographic heterogeneity across locations without geographic advantages or disadvantages. We propose an agent-based market model that considers a spectrum of different information-sharing mechanisms: no information sharing, information sharing among friends and pheromone-like information sharing. Finally, we build a unified model that accommodates all three of these information-sharing mechanisms based on the number of friends who can share information. We find that the no information-sharing model does not yield large economic zones, and more information sharing can give rise to a power-law distribution of market size that corresponds to the stylized fact of city size and firm size distributions. The simulations show that this model is robust. This paper provides an alternative approach to studying economic geographic development, and this model could be used as a test bed to validate the detailed assumptions that regulate real economic agglomeration. PMID:23484007

An event-triggered control approach for the leader-tracking problem with heterogeneous agents

NASA Astrophysics Data System (ADS)

Garcia, Eloy; Cao, Yongcan; Casbeer, David W.

2018-05-01

This paper presents an event-triggered control and communication framework for the cooperative leader-tracking problem with communication constraints. Continuous communication among agents is not assumed in this work and decentralised event-based strategies are proposed for agents with heterogeneous linear dynamics. Also, the leader dynamics are unknown and only intermittent measurements of its states are obtained by a subset of the followers. The event-based method not only represents a way to restrict communication among agents, but it also provides a decentralised scheme for scheduling information broadcasts. Notably, each agent is able to determine its own broadcasting instants independently of any other agent in the network. In an extension, the case where transmission of information is affected by time-varying communication delays is addressed. Finally, positive lower-bounds on the inter-event time intervals are obtained in order to show that Zeno behaviour does not exist and, therefore, continuous exchange of information is never needed in this framework.

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. © 2016 Mogilner and Manhart. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Discovery and Development of Natural Product-derived Chemotherapeutic Agents Based on a Medicinal Chemistry Approach⊥†

PubMed Central

Lee, Kuo-Hsiung

2010-01-01

Medicinal plants have long been an excellent source of pharmaceutical agents. Accordingly, the long term objectives of the author's research program are to discover and design new chemotherapeutic agents based on plant-derived compound leads by using a medicinal chemistry approach, which is a combination of chemistry and biology. Different examples of promising bioactive natural products and their synthetic analogs, including sesquiterpene lactones, quassinoids, naphthoquinones, phenylquinolones, dithiophenediones, neo-tanshinlactone, tylophorine, suksdorfin, DCK, and DCP, will be presented with respect to their discovery and preclinical development as potential clinical trial candidates. Research approaches include bioactivity- or mechanism of action-directed isolation and characterization of active compounds, rational drug design-based modification and analog synthesis, as well as structure-activity relationship and mechanism of action studies. Current clinical trials agents discovered by the Natural Products Research Laboratories, University of North Carolina, include bevirimat (dimethyl succinyl betulinic acid), which is now in Phase IIb trials for treating AIDS. Bevirimat is also the first in a new class of HIV drug candidates called “maturation inhibitors”. In addition, an etoposide analog, GL-331, progressed to anticancer Phase II clinical trials, and the curcumin analog JC-9 is in Phase II clinical trials for treating acne and in development for trials against prostate cancer. The discovery and development of these clinical trials candidates will also be discussed. PMID:20187635

Agent Model Development for Assessing Climate-Induced Geopolitical Instability.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boslough, Mark B.; Backus, George A.

2005-12-01

We present the initial stages of development of new agent-based computational methods to generate and test hypotheses about linkages between environmental change and international instability. This report summarizes the first year's effort of an originally proposed three-year Laboratory Directed Research and Development (LDRD) project. The preliminary work focused on a set of simple agent-based models and benefited from lessons learned in previous related projects and case studies of human response to climate change and environmental scarcity. Our approach was to define a qualitative model using extremely simple cellular agent models akin to Lovelock's Daisyworld and Schelling's segregation model. Such modelsmore » do not require significant computing resources, and users can modify behavior rules to gain insights. One of the difficulties in agent-based modeling is finding the right balance between model simplicity and real-world representation. Our approach was to keep agent behaviors as simple as possible during the development stage (described herein) and to ground them with a realistic geospatial Earth system model in subsequent years. This work is directed toward incorporating projected climate data--including various C02 scenarios from the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report--and ultimately toward coupling a useful agent-based model to a general circulation model.3« less

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…

An agent-based simulation combined with group decision-making technique for improving the performance of an emergency department.

PubMed

Yousefi, M; Ferreira, R P M

2017-03-30

This study presents an agent-based simulation modeling in an emergency department. In a traditional approach, a supervisor (or a manager) allocates the resources (receptionist, nurses, doctors, etc.) to different sections based on personal experience or by using decision-support tools. In this study, each staff agent took part in the process of allocating resources based on their observation in their respective sections, which gave the system the advantage of utilizing all the available human resources during the workday by being allocated to a different section. In this simulation, unlike previous studies, all staff agents took part in the decision-making process to re-allocate the resources in the emergency department. The simulation modeled the behavior of patients, receptionists, triage nurses, emergency room nurses and doctors. Patients were able to decide whether to stay in the system or leave the department at any stage of treatment. In order to evaluate the performance of this approach, 6 different scenarios were introduced. In each scenario, various key performance indicators were investigated before and after applying the group decision-making. The outputs of each simulation were number of deaths, number of patients who leave the emergency department without being attended, length of stay, waiting time and total number of discharged patients from the emergency department. Applying the self-organizing approach in the simulation showed an average of 12.7 and 14.4% decrease in total waiting time and number of patients who left without being seen, respectively. The results showed an average increase of 11.5% in total number of discharged patients from emergency department.

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.

Impacts of land-use management on ecosystem services and biodiversity: an agent-based modelling approach

PubMed Central

Heckbert, Scott; Wilson, Jeffrey J.; Vandenbroeck, Andrew J. K.; Cranston, Jerome; Farr, Daniel R.

2016-01-01

The science of ecosystem service (ES) mapping has become increasingly sophisticated over the past 20 years, and examples of successfully integrating ES into management decisions at national and sub-national scales have begun to emerge. However, increasing model sophistication and accuracy—and therefore complexity—may trade-off with ease of use and applicability to real-world decision-making contexts, so it is vital to incorporate the lessons learned from implementation efforts into new model development. Using successful implementation efforts for guidance, we developed an integrated ES modelling system to quantify several ecosystem services: forest timber production and carbon storage, water purification, pollination, and biodiversity. The system is designed to facilitate uptake of ES information into land-use decisions through three principal considerations: (1) using relatively straightforward models that can be readily deployed and interpreted without specialized expertise; (2) using an agent-based modelling framework to enable the incorporation of human decision-making directly within the model; and (3) integration among all ES models to simultaneously demonstrate the effects of a single land-use decision on multiple ES. We present an implementation of the model for a major watershed in Alberta, Canada, and highlight the system’s capabilities to assess a suite of ES under future management decisions, including forestry activities under two alternative timber harvest strategies, and through a scenario modelling analysis exploring different intensities of hypothetical agricultural expansion. By using a modular approach, the modelling system can be readily expanded to evaluate additional ecosystem services or management questions of interest in order to guide land-use decisions to achieve socioeconomic and environmental objectives. PMID:28028479

Agent-Based Framework for Personalized Service Provisioning in Converged IP Networks

NASA Astrophysics Data System (ADS)

Podobnik, Vedran; Matijasevic, Maja; Lovrek, Ignac; Skorin-Kapov, Lea; Desic, Sasa

In a global multi-service and multi-provider market, the Internet Service Providers will increasingly need to differentiate in the service quality they offer and base their operation on new, consumer-centric business models. In this paper, we propose an agent-based framework for the Business-to-Consumer (B2C) electronic market, comprising the Consumer Agents, Broker Agents and Content Agents, which enable Internet consumers to select a content provider in an automated manner. We also discuss how to dynamically allocate network resources to provide end-to-end Quality of Service (QoS) for a given consumer and content provider.

Situation awareness-based agent transparency for human-autonomy teaming effectiveness

NASA Astrophysics Data System (ADS)

Chen, Jessie Y. C.; Barnes, Michael J.; Wright, Julia L.; Stowers, Kimberly; Lakhmani, Shan G.

2017-05-01

We developed the Situation awareness-based Agent Transparency (SAT) model to support human operators' situation awareness of the mission environment through teaming with intelligent agents. The model includes the agent's current actions and plans (Level 1), its reasoning process (Level 2), and its projection of future outcomes (Level 3). Human-inthe-loop simulation experiments have been conducted (Autonomous Squad Member and IMPACT) to illustrate the utility of the model for human-autonomy team interface designs. Across studies, the results consistently showed that human operators' task performance improved as the agents became more transparent. They also perceived transparent agents as more trustworthy.

Vector-based navigation using grid-like representations in artificial agents.

PubMed

Banino, Andrea; Barry, Caswell; Uria, Benigno; Blundell, Charles; Lillicrap, Timothy; Mirowski, Piotr; Pritzel, Alexander; Chadwick, Martin J; Degris, Thomas; Modayil, Joseph; Wayne, Greg; Soyer, Hubert; Viola, Fabio; Zhang, Brian; Goroshin, Ross; Rabinowitz, Neil; Pascanu, Razvan; Beattie, Charlie; Petersen, Stig; Sadik, Amir; Gaffney, Stephen; King, Helen; Kavukcuoglu, Koray; Hassabis, Demis; Hadsell, Raia; Kumaran, Dharshan

2018-05-01

Deep neural networks have achieved impressive successes in fields ranging from object recognition to complex games such as Go 1,2 . Navigation, however, remains a substantial challenge for artificial agents, with deep neural networks trained by reinforcement learning 3-5 failing to rival the proficiency of mammalian spatial behaviour, which is underpinned by grid cells in the entorhinal cortex 6 . Grid cells are thought to provide a multi-scale periodic representation that functions as a metric for coding space 7,8 and is critical for integrating self-motion (path integration) 6,7,9 and planning direct trajectories to goals (vector-based navigation) 7,10,11 . Here we set out to leverage the computational functions of grid cells to develop a deep reinforcement learning agent with mammal-like navigational abilities. We first trained a recurrent network to perform path integration, leading to the emergence of representations resembling grid cells, as well as other entorhinal cell types 12 . We then showed that this representation provided an effective basis for an agent to locate goals in challenging, unfamiliar, and changeable environments-optimizing the primary objective of navigation through deep reinforcement learning. The performance of agents endowed with grid-like representations surpassed that of an expert human and comparison agents, with the metric quantities necessary for vector-based navigation derived from grid-like units within the network. Furthermore, grid-like representations enabled agents to conduct shortcut behaviours reminiscent of those performed by mammals. Our findings show that emergent grid-like representations furnish agents with a Euclidean spatial metric and associated vector operations, providing a foundation for proficient navigation. As such, our results support neuroscientific theories that see grid cells as critical for vector-based navigation 7,10,11 , demonstrating that the latter can be combined with path-based strategies to

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

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.

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.

OntoTrader: An Ontological Web Trading Agent Approach for Environmental Information Retrieval

PubMed Central

Iribarne, Luis; Padilla, Nicolás; Ayala, Rosa; Asensio, José A.; Criado, Javier

2014-01-01

Modern Web-based Information Systems (WIS) are becoming increasingly necessary to provide support for users who are in different places with different types of information, by facilitating their access to the information, decision making, workgroups, and so forth. Design of these systems requires the use of standardized methods and techniques that enable a common vocabulary to be defined to represent the underlying knowledge. Thus, mediation elements such as traders enrich the interoperability of web components in open distributed systems. These traders must operate with other third-party traders and/or agents in the system, which must also use a common vocabulary for communication between them. This paper presents the OntoTrader architecture, an Ontological Web Trading agent based on the OMG ODP trading standard. It also presents the ontology needed by some system agents to communicate with the trading agent and the behavioral framework for the SOLERES OntoTrader agent, an Environmental Management Information System (EMIS). This framework implements a “Query-Searching/Recovering-Response” information retrieval model using a trading service, SPARQL notation, and the JADE platform. The paper also presents reflection, delegation and, federation mediation models and describes formalization, an experimental testing environment in three scenarios, and a tool which allows our proposal to be evaluated and validated. PMID:24977211

OntoTrader: an ontological Web trading agent approach for environmental information retrieval.

PubMed

Iribarne, Luis; Padilla, Nicolás; Ayala, Rosa; Asensio, José A; Criado, Javier

2014-01-01

Modern Web-based Information Systems (WIS) are becoming increasingly necessary to provide support for users who are in different places with different types of information, by facilitating their access to the information, decision making, workgroups, and so forth. Design of these systems requires the use of standardized methods and techniques that enable a common vocabulary to be defined to represent the underlying knowledge. Thus, mediation elements such as traders enrich the interoperability of web components in open distributed systems. These traders must operate with other third-party traders and/or agents in the system, which must also use a common vocabulary for communication between them. This paper presents the OntoTrader architecture, an Ontological Web Trading agent based on the OMG ODP trading standard. It also presents the ontology needed by some system agents to communicate with the trading agent and the behavioral framework for the SOLERES OntoTrader agent, an Environmental Management Information System (EMIS). This framework implements a "Query-Searching/Recovering-Response" information retrieval model using a trading service, SPARQL notation, and the JADE platform. The paper also presents reflection, delegation and, federation mediation models and describes formalization, an experimental testing environment in three scenarios, and a tool which allows our proposal to be evaluated and validated.

Efficient Agent-Based Models for Non-Genomic Evolution

NASA Technical Reports Server (NTRS)

Gupta, Nachi; Agogino, Adrian; Tumer, Kagan

2006-01-01

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sukumar, Sreenivas R; Nutaro, James J

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 paradigmmore » to another. We conclude with a discussion of our experience and document future ideas for a model validation framework.« less

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

DTIC Science & Technology

2013-03-29

Assessor that is in the SoS agent. Figure 31. Fuzzy Assessor for the SoS Agent for Assessment of SoS Architecture «subsystem» Fuzzy Rules « datatype ...Affordability « datatype » Flexibility « datatype » Performance « datatype » Robustness Input Input Input Input « datatype » Architecture QualityOutput Fuzzy

Issues of Dynamic Coalition Formation Among Rational Agents

DTIC Science & Technology

2002-04-01

approaches of forming stable coalitions among rational agents. Issues and problems of dynamic coalition environments are discussed in section 3 while...2.2. 2.1.2 Coalition Algorithm, Coalition Formation Environment and Model Rational agents which are involved in a co-operative game (A,v) are...publicly available simulation environment for coalition formation among rational information agents based on selected classic coalition theories is, for

Towards a framework for agent-based image analysis of remote-sensing data

PubMed Central

Hofmann, Peter; Lettmayer, Paul; Blaschke, Thomas; Belgiu, Mariana; Wegenkittl, Stefan; Graf, Roland; Lampoltshammer, Thomas Josef; Andrejchenko, Vera

2015-01-01

Object-based image analysis (OBIA) as a paradigm for analysing remotely sensed image data has in many cases led to spatially and thematically improved classification results in comparison to pixel-based approaches. Nevertheless, robust and transferable object-based solutions for automated image analysis capable of analysing sets of images or even large image archives without any human interaction are still rare. A major reason for this lack of robustness and transferability is the high complexity of image contents: Especially in very high resolution (VHR) remote-sensing data with varying imaging conditions or sensor characteristics, the variability of the objects’ properties in these varying images is hardly predictable. The work described in this article builds on so-called rule sets. While earlier work has demonstrated that OBIA rule sets bear a high potential of transferability, they need to be adapted manually, or classification results need to be adjusted manually in a post-processing step. In order to automate these adaptation and adjustment procedures, we investigate the coupling, extension and integration of OBIA with the agent-based paradigm, which is exhaustively investigated in software engineering. The aims of such integration are (a) autonomously adapting rule sets and (b) image objects that can adopt and adjust themselves according to different imaging conditions and sensor characteristics. This article focuses on self-adapting image objects and therefore introduces a framework for agent-based image analysis (ABIA). PMID:27721916

Clustering recommendations to compute agent reputation

NASA Astrophysics Data System (ADS)

Bedi, Punam; Kaur, Harmeet

2005-03-01

Traditional centralized approaches to security are difficult to apply to multi-agent systems which are used nowadays in e-commerce applications. Developing a notion of trust that is based on the reputation of an agent can provide a softer notion of security that is sufficient for many multi-agent applications. Our paper proposes a mechanism for computing reputation of the trustee agent for use by the trustier agent. The trustier agent computes the reputation based on its own experience as well as the experience the peer agents have with the trustee agents. The trustier agents intentionally interact with the peer agents to get their experience information in the form of recommendations. We have also considered the case of unintentional encounters between the referee agents and the trustee agent, which can be directly between them or indirectly through a set of interacting agents. The clustering is done to filter off the noise in the recommendations in the form of outliers. The trustier agent clusters the recommendations received from referee agents on the basis of the distances between recommendations using the hierarchical agglomerative method. The dendogram hence obtained is cut at the required similarity level which restricts the maximum distance between any two recommendations within a cluster. The cluster with maximum number of elements denotes the views of the majority of recommenders. The center of this cluster represents the reputation of the trustee agent which can be computed using c-means algorithm.

Gadolinium-based magnetic resonance imaging contrast agents in interventional radiology.

PubMed

Atar, Eli

2004-07-01

Gadolinium-based agents are widely used in magnetic resonance imaging as contrast agents. These agents are radio-opaque enough for diagnostic imaging of the vascular tree by using digitally subtracted images as well as for imaging of the biliary system and the urinary tract. The recommended doses for gadolinium do not impair renal function or cause adverse reactions in patients with iodine sensitivity; thus patients with such conditions can safely undergo diagnostic angiography, either by MRI angiography or by catheterization using gadolinium as contrast agent, for diagnostic and therapeutic purposes.

Advanced Approach of Multiagent Based Buoy Communication

PubMed Central

Gricius, Gediminas; Drungilas, Darius; Dzemydiene, Dale

2015-01-01

Usually, a hydrometeorological information system is faced with great data flows, but the data levels are often excessive, depending on the observed region of the water. The paper presents advanced buoy communication technologies based on multiagent interaction and data exchange between several monitoring system nodes. The proposed management of buoy communication is based on a clustering algorithm, which enables the performance of the hydrometeorological information system to be enhanced. The experiment is based on the design and analysis of the inexpensive but reliable Baltic Sea autonomous monitoring network (buoys), which would be able to continuously monitor and collect temperature, waviness, and other required data. The proposed approach of multiagent based buoy communication enables all the data from the costal-based station to be monitored with limited transition speed by setting different tasks for the agent-based buoy system according to the clustering information. PMID:26345197

Multi-agent cooperation rescue algorithm based on influence degree and state prediction

NASA Astrophysics Data System (ADS)

Zheng, Yanbin; Ma, Guangfu; Wang, Linlin; Xi, Pengxue

2018-04-01

Aiming at the multi-agent cooperative rescue in disaster, a multi-agent cooperative rescue algorithm based on impact degree and state prediction is proposed. Firstly, based on the influence of the information in the scene on the collaborative task, the influence degree function is used to filter the information. Secondly, using the selected information to predict the state of the system and Agent behavior. Finally, according to the result of the forecast, the cooperative behavior of Agent is guided and improved the efficiency of individual collaboration. The simulation results show that this algorithm can effectively solve the cooperative rescue problem of multi-agent and ensure the efficient completion of the task.

Persuasion Model and Its Evaluation Based on Positive Change Degree of Agent Emotion

NASA Astrophysics Data System (ADS)

Jinghua, Wu; Wenguang, Lu; Hailiang, Meng

For it can meet needs of negotiation among organizations take place in different time and place, and for it can make its course more rationality and result more ideal, persuasion based on agent can improve cooperation among organizations well. Integrated emotion change in agent persuasion can further bring agent advantage of artificial intelligence into play. Emotion of agent persuasion is classified, and the concept of positive change degree is given. Based on this, persuasion model based on positive change degree of agent emotion is constructed, which is explained clearly through an example. Finally, the method of relative evaluation is given, which is also verified through a calculation example.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gallo, Giulia

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.

An agent-based simulation combined with group decision-making technique for improving the performance of an emergency department

PubMed Central

Yousefi, M.; Ferreira, R.P.M.

2017-01-01

This study presents an agent-based simulation modeling in an emergency department. In a traditional approach, a supervisor (or a manager) allocates the resources (receptionist, nurses, doctors, etc.) to different sections based on personal experience or by using decision-support tools. In this study, each staff agent took part in the process of allocating resources based on their observation in their respective sections, which gave the system the advantage of utilizing all the available human resources during the workday by being allocated to a different section. In this simulation, unlike previous studies, all staff agents took part in the decision-making process to re-allocate the resources in the emergency department. The simulation modeled the behavior of patients, receptionists, triage nurses, emergency room nurses and doctors. Patients were able to decide whether to stay in the system or leave the department at any stage of treatment. In order to evaluate the performance of this approach, 6 different scenarios were introduced. In each scenario, various key performance indicators were investigated before and after applying the group decision-making. The outputs of each simulation were number of deaths, number of patients who leave the emergency department without being attended, length of stay, waiting time and total number of discharged patients from the emergency department. Applying the self-organizing approach in the simulation showed an average of 12.7 and 14.4% decrease in total waiting time and number of patients who left without being seen, respectively. The results showed an average increase of 11.5% in total number of discharged patients from emergency department. PMID:28380196

An Evolvable Multi-Agent Approach to Space Operations Engineering

NASA Technical Reports Server (NTRS)

Mandutianu, Sanda; Stoica, Adrian

1999-01-01

A complex system of spacecraft and ground tracking stations, as well as a constellation of satellites or spacecraft, has to be able to reliably withstand sudden environment changes, resource fluctuations, dynamic resource configuration, limited communication bandwidth, etc., while maintaining the consistency of the system as a whole. It is not known in advance when a change in the environment might occur or when a particular exchange will happen. A higher degree of sophistication for the communication mechanisms between different parts of the system is required. The actual behavior has to be determined while the system is performing and the course of action can be decided at the individual level. Under such circumstances, the solution will highly benefit from increased on-board and on the ground adaptability and autonomy. An evolvable architecture based on intelligent agents that communicate and cooperate with each other can offer advantages in this direction. This paper presents an architecture of an evolvable agent-based system (software and software/hardware hybrids) as well as some plans for further implementation.

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

PubMed

Stivala, Alex

2017-06-01

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. © Society for Community Research and Action 2017.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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 themore » importance of modeling decisions that are often overlooked.« less

Modelling the Transport of Nanoparticles under Blood Flow using an Agent-based Approach.

PubMed

Fullstone, Gavin; Wood, Jonathan; Holcombe, Mike; Battaglia, Giuseppe

2015-06-10

Blood-mediated nanoparticle delivery is a new and growing field in the development of therapeutics and diagnostics. Nanoparticle properties such as size, shape and surface chemistry can be controlled to improve their performance in biological systems. This enables modulation of immune system interactions, blood clearance profile and interaction with target cells, thereby aiding effective delivery of cargo within cells or tissues. Their ability to target and enter tissues from the blood is highly dependent on their behaviour under blood flow. Here we have produced an agent-based model of nanoparticle behaviour under blood flow in capillaries. We demonstrate that red blood cells are highly important for effective nanoparticle distribution within capillaries. Furthermore, we use this model to demonstrate how nanoparticle size can selectively target tumour tissue over normal tissue. We demonstrate that the polydispersity of nanoparticle populations is an important consideration in achieving optimal specificity and to avoid off-target effects. In future this model could be used for informing new nanoparticle design and to predict general and specific uptake properties under blood flow.

Redox-activated MRI contrast agents based on lanthanide and transition metal ions.

PubMed

Tsitovich, Pavel B; Burns, Patrick J; McKay, Adam M; Morrow, Janet R

2014-04-01

The reduction/oxidation (redox) potential of tissue is tightly regulated in order to maintain normal physiological processes, but is disrupted in disease states. Thus, the development of new tools to map tissue redox potential may be clinically important for the diagnosis of diseases that lead to redox imbalances. One promising area of chemical research is the development of redox-activated probes for mapping tissue through magnetic resonance imaging (MRI). In this review, we summarize several strategies for the design of redox-responsive MRI contrast agents. Our emphasis is on both lanthanide(III) and transition metal(II/III) ion complexes that provide contrast either as T1 relaxivity MRI contrast agents or as paramagnetic chemical exchange saturation transfer (PARACEST) contrast agents. These agents are redox-triggered by a variety of chemical reactions or switches including redox-activated thiol groups, and heterocyclic groups that interact with the metal ion or influence properties of other ancillary ligands. Metal ion centered redox is an approach which is ripe for development by coordination chemists. Redox-triggered metal ion approaches have great potential for creating large differences in magnetic properties that lead to changes in contrast. An attractive feature of these agents is the ease of fine-tuning the metal ion redox potential over a biologically relevant range. Copyright © 2014 Elsevier Inc. All rights reserved.

Personalized E- learning System Based on Intelligent Agent

NASA Astrophysics Data System (ADS)

Duo, Sun; Ying, Zhou Cai

Lack of personalized learning is the key shortcoming of traditional e-Learning system. This paper analyzes the personal characters in e-Learning activity. In order to meet the personalized e-learning, a personalized e-learning system based on intelligent agent was proposed and realized in the paper. The structure of system, work process, the design of intelligent agent and the realization of intelligent agent were introduced in the paper. After the test use of the system by certain network school, we found that the system could improve the learner's initiative participation, which can provide learners with personalized knowledge service. Thus, we thought it might be a practical solution to realize self- learning and self-promotion in the lifelong education age.

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

PubMed

Anderson, Christine A; Titler, Marita G

2014-09-27

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

Intelligent Agent Architectures: Reactive Planning Testbed

NASA Technical Reports Server (NTRS)

Rosenschein, Stanley J.; Kahn, Philip

1993-01-01

An Integrated Agent Architecture (IAA) is a framework or paradigm for constructing intelligent agents. Intelligent agents are collections of sensors, computers, and effectors that interact with their environments in real time in goal-directed ways. Because of the complexity involved in designing intelligent agents, it has been found useful to approach the construction of agents with some organizing principle, theory, or paradigm that gives shape to the agent's components and structures their relationships. Given the wide variety of approaches being taken in the field, the question naturally arises: Is there a way to compare and evaluate these approaches? The purpose of the present work is to develop common benchmark tasks and evaluation metrics to which intelligent agents, including complex robotic agents, constructed using various architectural approaches can be subjected.

Density Control of Multi-Agent Systems with Safety Constraints: A Markov Chain Approach

NASA Astrophysics Data System (ADS)

Demirer, Nazli

The control of systems with autonomous mobile agents has been a point of interest recently, with many applications like surveillance, coverage, searching over an area with probabilistic target locations or exploring an area. In all of these applications, the main goal of the swarm is to distribute itself over an operational space to achieve mission objectives specified by the density of swarm. This research focuses on the problem of controlling the distribution of multi-agent systems considering a hierarchical control structure where the whole swarm coordination is achieved at the high-level and individual vehicle/agent control is managed at the low-level. High-level coordination algorithms uses macroscopic models that describes the collective behavior of the whole swarm and specify the agent motion commands, whose execution will lead to the desired swarm behavior. The low-level control laws execute the motion to follow these commands at the agent level. The main objective of this research is to develop high-level decision control policies and algorithms to achieve physically realizable commanding of the agents by imposing mission constraints on the distribution. We also make some connections with decentralized low-level motion control. This dissertation proposes a Markov chain based method to control the density distribution of the whole system where the implementation can be achieved in a decentralized manner with no communication between agents since establishing communication with large number of agents is highly challenging. The ultimate goal is to guide the overall density distribution of the system to a prescribed steady-state desired distribution while satisfying desired transition and safety constraints. Here, the desired distribution is determined based on the mission requirements, for example in the application of area search, the desired distribution should match closely with the probabilistic target locations. The proposed method is applicable for both

A Unified Approach to Model-Based Planning and Execution

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Dorais, Gregory A.; Fry, Chuck; Levinson, Richard; Plaunt, Christian; Norvig, Peter (Technical Monitor)

2000-01-01

Writing autonomous software is complex, requiring the coordination of functionally and technologically diverse software modules. System and mission engineers must rely on specialists familiar with the different software modules to translate requirements into application software. Also, each module often encodes the same requirement in different forms. The results are high costs and reduced reliability due to the difficulty of tracking discrepancies in these encodings. In this paper we describe a unified approach to planning and execution that we believe provides a unified representational and computational framework for an autonomous agent. We identify the four main components whose interplay provides the basis for the agent's autonomous behavior: the domain model, the plan database, the plan running module, and the planner modules. This representational and problem solving approach can be applied at all levels of the architecture of a complex agent, such as Remote Agent. In the rest of the paper we briefly describe the Remote Agent architecture. The new agent architecture proposed here aims at achieving the full Remote Agent functionality. We then give the fundamental ideas behind the new agent architecture and point out some implication of the structure of the architecture, mainly in the area of reactivity and interaction between reactive and deliberative decision making. We conclude with related work and current status.

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.

Development and Evaluation of Intelligent Agent-Based Teaching Assistant in e-Learning Portals

ERIC Educational Resources Information Center

Rouhani, Saeed; Mirhosseini, Seyed Vahid

2015-01-01

Today, several educational portals established by organizations to enhance web E-learning. Intelligence agent's usage is necessary to improve the system's quality and cover limitations such as face-to-face relation. In this research, after finding two main approaches in this field that are fundamental use of intelligent agents in systems design…

Research on environmental impact of water-based fire extinguishing agents

NASA Astrophysics Data System (ADS)

Wang, Shuai

2018-02-01

This paper offers current status of application of water-based fire extinguishing agents, the environmental and research considerations of the need for the study of toxicity research. This paper also offers systematic review of test methods of toxicity and environmental impact of water-based fire extinguishing agents currently available, illustrate the main requirements and relevant test methods, and offer some research findings for future research considerations. The paper also offers limitations of current study.

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

Complex systems approach to scientific publication and peer-review system: development of an agent-based model calibrated with empirical journal data.

PubMed

Kovanis, Michail; Porcher, Raphaël; Ravaud, Philippe; Trinquart, Ludovic

Scientific peer-review and publication systems incur a huge burden in terms of costs and time. Innovative alternatives have been proposed to improve the systems, but assessing their impact in experimental studies is not feasible at a systemic level. We developed an agent-based model by adopting a unified view of peer review and publication systems and calibrating it with empirical journal data in the biomedical and life sciences. We modeled researchers, research manuscripts and scientific journals as agents. Researchers were characterized by their scientific level and resources, manuscripts by their scientific value, and journals by their reputation and acceptance or rejection thresholds. These state variables were used in submodels for various processes such as production of articles, submissions to target journals, in-house and external peer review, and resubmissions. We collected data for a sample of biomedical and life sciences journals regarding acceptance rates, resubmission patterns and total number of published articles. We adjusted submodel parameters so that the agent-based model outputs fit these empirical data. We simulated 105 journals, 25,000 researchers and 410,000 manuscripts over 10 years. A mean of 33,600 articles were published per year; 19 % of submitted manuscripts remained unpublished. The mean acceptance rate was 21 % after external peer review and rejection rate 32 % after in-house review; 15 % publications resulted from the first submission, 47 % the second submission and 20 % the third submission. All decisions in the model were mainly driven by the scientific value, whereas journal targeting and persistence in resubmission defined whether a manuscript would be published or abandoned after one or many rejections. This agent-based model may help in better understanding the determinants of the scientific publication and peer-review systems. It may also help in assessing and identifying the most promising alternative systems of peer

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

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.

The value of less connected agents in Boolean networks

NASA Astrophysics Data System (ADS)

Epstein, Daniel; Bazzan, Ana L. C.

2013-11-01

In multiagent systems, agents often face binary decisions where one seeks to take either the minority or the majority side. Examples are minority and congestion games in general, i.e., situations that require coordination among the agents in order to depict efficient decisions. In minority games such as the El Farol Bar Problem, previous works have shown that agents may reach appropriate levels of coordination, mostly by looking at the history of past decisions. Not many works consider any kind of structure of the social network, i.e., how agents are connected. Moreover, when structure is indeed considered, it assumes some kind of random network with a given, fixed connectivity degree. The present paper departs from the conventional approach in some ways. First, it considers more realistic network topologies, based on preferential attachments. This is especially useful in social networks. Second, the formalism of random Boolean networks is used to help agents to make decisions given their attachments (for example acquaintances). This is coupled with a reinforcement learning mechanism that allows agents to select strategies that are locally and globally efficient. Third, we use agent-based modeling and simulation, a microscopic approach, which allows us to draw conclusions about individuals and/or classes of individuals. Finally, for the sake of illustration we use two different scenarios, namely the El Farol Bar Problem and a binary route choice scenario. With this approach we target systems that adapt dynamically to changes in the environment, including other adaptive decision-makers. Our results using preferential attachments and random Boolean networks are threefold. First we show that an efficient equilibrium can be achieved, provided agents do experimentation. Second, microscopic analysis show that influential agents tend to consider few inputs in their Boolean functions. Third, we have also conducted measurements related to network clustering and centrality

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

Intelligent agent-based intrusion detection system using enhanced multiclass SVM.

PubMed

Ganapathy, S; Yogesh, P; Kannan, A

2012-01-01

Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set.

Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM

PubMed Central

Ganapathy, S.; Yogesh, P.; Kannan, A.

2012-01-01

Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set. PMID:23056036

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.

A multimethod approach to examining usability of Web privacy polices and user agents for specifying privacy preferences.

PubMed

Proctor, Robert W; Vu, Kim-Phuong L

2007-05-01

Because all research methods have strengths and weaknesses, a multimethod approach often provides the best way to understand human behavior in applied settings. We describe how a multimethod approach was employed in a series of studies designed to examine usability issues associated with two aspects of online privacy: comprehension of privacy policies and configuration of privacy preferences for an online user agent. Archival research, user surveys, data mining, quantitative observations, and controlled experiments each yielded unique findings that, together, contributed to increased understanding of online-privacy issues for users. These findings were used to evaluate the accessibility of Web privacy policies to computer-literate users, determine whether people can configure user agents to achieve specific privacy goals, and discover ways in which the usability of those agents can be improved.

Effects of Cueing by a Pedagogical Agent in an Instructional Animation: A Cognitive Load Approach

ERIC Educational Resources Information Center

Yung, Hsin I.; Paas, Fred

2015-01-01

This study investigated the effects of a pedagogical agent that cued relevant information in a story-based instructional animation on the cardiovascular system. Based on cognitive load theory, it was expected that the experimental condition with the pedagogical agent would facilitate students to distinguish between relevant and irrelevant…

Knowledge Management in Role Based Agents

NASA Astrophysics Data System (ADS)

Kır, Hüseyin; Ekinci, Erdem Eser; Dikenelli, Oguz

In multi-agent system literature, the role concept is getting increasingly researched to provide an abstraction to scope beliefs, norms, goals of agents and to shape relationships of the agents in the organization. In this research, we propose a knowledgebase architecture to increase applicability of roles in MAS domain by drawing inspiration from the self concept in the role theory of sociology. The proposed knowledgebase architecture has granulated structure that is dynamically organized according to the agent's identification in a social environment. Thanks to this dynamic structure, agents are enabled to work on consistent knowledge in spite of inevitable conflicts between roles and the agent. The knowledgebase architecture is also implemented and incorporated into the SEAGENT multi-agent system development framework.

Natural Humic-Acid-Based Phototheranostic Agent.

PubMed

Miao, Zhao-Hua; Li, Kai; Liu, Pei-Ying; Li, Zhenglin; Yang, Huanjie; Zhao, Qingliang; Chang, Manli; Yang, Qingzhu; Zhen, Liang; Xu, Cheng-Yan

2018-04-01

Humic acids, a major constituent of natural organic carbon resources, are naturally formed through the microbial biodegradation of animal and plant residues. Due to numerous physiologically active groups (phenol, carboxyl, and quinone), the biomedical applications of humic acid have been already investigated across different cultures for several centuries or even longer. In this work, sodium humate, the sodium salt of humic acid, is explored as phototheranostic agent for light-induced photoacoustic imaging and photothermal therapy based on intrinsic absorption in the near-infrared region. The purified colloidal sodium humate exhibits a high photothermal conversion efficiency up to 76.3%, much higher than that of the majority of state-of-the-art photothermal agents including gold nanorods, Cu 9 S 5 nanoparticles, antimonene quantum dots, and black phosphorus quantum dots, leading to obvious photoacoustic enhancement in vitro and in vivo. Besides, highly effective photothermal ablation of HeLa tumor is achieved through intratumoral injection. Impressively, sodium humate reveals ultralow toxicity at the cellular and animal levels. This work promises the great potential of humic acids as light-mediated theranostic agents, thus expanding the application scope of traditional humic acids in biomedical field. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Protein Aggregation Based Test for Screening of the Agents Affecting Thermostability of Proteins

PubMed Central

Eronina, Tatyana; Borzova, Vera; Maloletkina, Olga; Kleymenov, Sergey; Asryants, Regina; Markossian, Kira; Kurganov, Boris

2011-01-01

To search for agents affecting thermal stability of proteins, a test based on the registration of protein aggregation in the regime of heating with a constant rate was used. The initial parts of the dependences of the light scattering intensity (I) on temperature (T) were analyzed using the following empiric equation: I = K agg(T−T 0)2, where K agg is the parameter characterizing the initial rate of aggregation and T 0 is a temperature at which the initial increase in the light scattering intensity is registered. The aggregation data are interpreted in the frame of the model assuming the formation of the start aggregates at the initial stages of the aggregation process. Parameter T 0 corresponds to the moment of the origination of the start aggregates. The applicability of the proposed approach was demonstrated on the examples of thermal aggregation of glycogen phosphorylase b from rabbit skeletal muscles and bovine liver glutamate dehydrogenase studied in the presence of agents of different chemical nature. The elaborated approach to the study of protein aggregation may be used for rapid identification of small molecules that interact with protein targets. PMID:21760963

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.

Nature-based molecules combined with rivastigmine: A symbiotic approach for the synthesis of new agents against Alzheimer's disease.

PubMed

Nesi, Giulia; Chen, Qiuhe; Sestito, Simona; Digiacomo, Maria; Yang, Xiaohong; Wang, Shengnan; Pi, Rongbiao; Rapposelli, Simona

2017-12-01

Starting from nature as original source, new potential agents with pleiotropic activities have been synthesized and evaluated as neuroprotective agents. In this work, novel nature-based hybrids, combining antioxidant motifs with rivastigmine, have been designed and synthesized. The biological results revealed that the new compounds inhibit both AChE and BuChE. In particular, lipoic acid hybrids LA1, LA2, LA3 resulted to be the most potent inhibitors of BuChE showing IC 50 values ranging from 340 to 378 nM. Analogously, all the compounds were able to inhibit the self β-amyloid 1-42 aggregation. The gallic acid hybrid GA2 as well as the 2-chromonecarboxylic acid hybrids CA1 and CA2 prevented the self-mediated Aβ aggregation with percentages of inhibition ranging from 53% to 59%. Finally, some of them also show potent neuroprotective effects against glutamate-induced cell death and low toxicity in HT22 cells. Copyright © 2017. Published by Elsevier Masson SAS.

Evolutions in fragment-based drug design: the deconstruction–reconstruction approach

PubMed Central

Chen, Haijun; Zhou, Xiaobin; Wang, Ailan; Zheng, Yunquan; Gao, Yu; Zhou, Jia

2014-01-01

Recent advances in the understanding of molecular recognition and protein–ligand interactions have facilitated rapid development of potent and selective ligands for therapeutically relevant targets. Over the past two decades, a variety of useful approaches and emerging techniques have been developed to promote the identification and optimization of leads that have high potential for generating new therapeutic agents. Intriguingly, the innovation of a fragment-based drug design (FBDD) approach has enabled rapid and efficient progress in drug discovery. In this critical review, we focus on the construction of fragment libraries and the advantages and disadvantages of various fragment-based screening (FBS) for constructing such libraries. We also highlight the deconstruction–reconstruction strategy by utilizing privileged fragments of reported ligands. PMID:25263697

Progress in the development of peroxide-based anti-parasitic agents.

PubMed

Muraleedharan, K M; Avery, Mitchell A

2009-08-01

Progress made in the past decade pertaining to the development of anti-parasitic agents based on artemisinin is presented. Apart from discussions on important derivatives obtained through functionalization at the C-3, C-9, C-10 and O-11 positions of artemisinin, an outline on its seco analogs and artemisinin bundles are given for a broader perspective on structure-activity relationships. Success with synthetic peroxides, drug-hybrid approaches, broad-spectrum anti-infective properties of peroxide compounds and a survey on peroxide-containing natural products other than artemisinin with available biological data are included to highlight recent trends and avenues for future research. A supplementary material with details on the biological properties of a larger collection of molecules belonging to the above structural classes is also given for reference.

A New HIV Prevention Network Approach: Sociometric Peer Change Agent Selection

PubMed Central

Schneider, John A.; Zhou, A. Ning; Laumann, Edward O.

2014-01-01

Internationally, the Peer Change Agent (PCA) model is the most frequently used conceptual framework for HIV prevention. Change agents themselves can be more important than the messages they convey. PCA selection is operationalized via heterogeneous methods based upon individual-level attributes. A sociometric position selection strategy, however, could increase peer influence potency and halt transmission at key network locations. In this study, we selected candidate PCAs based upon relative sociometric bridging and centrality scores and assessed their attributes in comparison to one another and to existing peer educators. We focused upon an emerging HIV epidemic among men who have sex with men in Southern India in 2011. PCAs selected based on their bridging score were more likely to be innovators when compared to other centrally-located PCAs, to PCAs located on the periphery, and to existing peer educators. We also found that sociodemographic attributes and risk behaviors were similar across all candidate PCAs, but risk behaviors of existing peer educators differed. Existing peer educators were more likely to engage in higher risk behavior such as receiving money for sex when compared to sociometrically selected peer changes agents. These existing peer educators were also more likely to exhibit leadership qualities within the overall network; they were, however, just as likely as other non-trained candidate peer change agents to report important HIV intravention behavior (encouraging condoms within their network). The importance of identifying bridges who may be able to diffuse innovation more effectively within high risk HIV networks is especially critical given recent efficacy data from novel HIV prevention interventions such as pre-exposure prophylaxis. Moreover, while existing peer educators were more likely to be leaders in our analysis, using peer educators with high risk behavior may have limited utility in enacting behavior change among sex worker peers or

Simulation-based intelligent robotic agent for Space Station Freedom

NASA Technical Reports Server (NTRS)

Biegl, Csaba A.; Springfield, James F.; Cook, George E.; Fernandez, Kenneth R.

1990-01-01

A robot control package is described which utilizes on-line structural simulation of robot manipulators and objects in their workspace. The model-based controller is interfaced with a high level agent-independent planner, which is responsible for the task-level planning of the robot's actions. Commands received from the agent-independent planner are refined and executed in the simulated workspace, and upon successful completion, they are transferred to the real manipulators.

Agent-Based Scientific Workflow Composition

NASA Astrophysics Data System (ADS)

Barker, A.; Mann, B.

2006-07-01

Agents are active autonomous entities that interact with one another to achieve their objectives. This paper addresses how these active agents are a natural fit to consume the passive Service Oriented Architecture which is found in Internet and Grid Systems, in order to compose, coordinate and execute e-Science experiments. A framework is introduced which allows an e-Science experiment to be described as a MultiAgent System.

Multiscale agent-based cancer modeling.

PubMed

Zhang, Le; Wang, Zhihui; Sagotsky, Jonathan A; Deisboeck, Thomas S

2009-04-01

Agent-based modeling (ABM) is an in silico technique that is being used in a variety of research areas such as in social sciences, economics and increasingly in biomedicine as an interdisciplinary tool to study the dynamics of complex systems. Here, we describe its applicability to integrative tumor biology research by introducing a multi-scale tumor modeling platform that understands brain cancer as a complex dynamic biosystem. We summarize significant findings of this work, and discuss both challenges and future directions for ABM in the field of cancer research.

Agent-Based Simulation for Interconnection-Scale Renewable Integration and Demand Response Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chassin, David P.; Behboodi, Sahand; Crawford, Curran

This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integration of renewable generation and controllable loads. Approaches for modeling aggregated controllable loads are presented and placed in the same control and economic modeling framework as generation resources for interconnection planning studies. Model performance is examined with system parameters that are typical for an interconnection approximately the size of the Western Electricity Coordinating Council (WECC) and a control area about 1/100 the size of the system. These results are used to demonstrate and validate the methodsmore » presented.« less

Agent-Based Simulation for Interconnection-Scale Renewable Integration and Demand Response Studies

DOE PAGES

Chassin, David P.; Behboodi, Sahand; Crawford, Curran; ...

2015-12-23

This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integration of renewable generation and controllable loads. Approaches for modeling aggregated controllable loads are presented and placed in the same control and economic modeling framework as generation resources for interconnection planning studies. Model performance is examined with system parameters that are typical for an interconnection approximately the size of the Western Electricity Coordinating Council (WECC) and a control area about 1/100 the size of the system. These results are used to demonstrate and validate the methodsmore » presented.« less

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

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.

Consensus pursuit of heterogeneous multi-agent systems under a directed acyclic graph

NASA Astrophysics Data System (ADS)

Yan, Jing; Guan, Xin-Ping; Luo, Xiao-Yuan

2011-04-01

This paper is concerned with the cooperative target pursuit problem by multiple agents based on directed acyclic graph. The target appears at a random location and moves only when sensed by the agents, and agents will pursue the target once they detect its existence. Since the ability of each agent may be different, we consider the heterogeneous multi-agent systems. According to the topology of the multi-agent systems, a novel consensus-based control law is proposed, where the target and agents are modeled as a leader and followers, respectively. Based on Mason's rule and signal flow graph analysis, the convergence conditions are provided to show that the agents can catch the target in a finite time. Finally, simulation studies are provided to verify the effectiveness of the proposed approach.

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…

Unsilencing Critical Conversations in Social-Studies Teacher Education Using Agent-Based Modeling

ERIC Educational Resources Information Center

Hostetler, Andrew; Sengupta, Pratim; Hollett, Ty

2018-01-01

In this article, we argue that when complex sociopolitical issues such as ethnocentrism and racial segregation are represented as complex, emergent systems using agent-based computational models (in short agent-based models or ABMs), discourse about these representations can disrupt social studies teacher candidates' dispositions of teaching…

Agent-Based Models in Empirical Social Research

ERIC Educational Resources Information Center

Bruch, Elizabeth; Atwell, Jon

2015-01-01

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

Organization of the secure distributed computing based on multi-agent system

NASA Astrophysics Data System (ADS)

Khovanskov, Sergey; Rumyantsev, Konstantin; Khovanskova, Vera

2018-04-01

Nowadays developing methods for distributed computing is received much attention. One of the methods of distributed computing is using of multi-agent systems. The organization of distributed computing based on the conventional network computers can experience security threats performed by computational processes. Authors have developed the unified agent algorithm of control system of computing network nodes operation. Network PCs is used as computing nodes. The proposed multi-agent control system for the implementation of distributed computing allows in a short time to organize using of the processing power of computers any existing network to solve large-task by creating a distributed computing. Agents based on a computer network can: configure a distributed computing system; to distribute the computational load among computers operated agents; perform optimization distributed computing system according to the computing power of computers on the network. The number of computers connected to the network can be increased by connecting computers to the new computer system, which leads to an increase in overall processing power. Adding multi-agent system in the central agent increases the security of distributed computing. This organization of the distributed computing system reduces the problem solving time and increase fault tolerance (vitality) of computing processes in a changing computing environment (dynamic change of the number of computers on the network). Developed a multi-agent system detects cases of falsification of the results of a distributed system, which may lead to wrong decisions. In addition, the system checks and corrects wrong results.

Forbidding Undesirable Agreements: A Dependence-Based Approach to the Regulation of Multi-agent Systems

NASA Astrophysics Data System (ADS)

Turrini, Paolo; Grossi, Davide; Broersen, Jan; Meyer, John-Jules Ch.

The purpose of this contribution is to set up a language to evaluate the results of concerted action among interdependent agents against predetermined properties that we can recognise as desirable from a deontic point of view. Unlike the standard view of logics to reason about coalitionally rational action, the capacity of a set of agents to take a rational decision will be restricted to what we will call agreements, that can be seen as solution concepts to a dependence structure present in a certain game. The language will identify in concise terms those agreements that act accordingly or disaccordingly with the desirable properties arbitrarily set up in the beginning, and will reveal, by logical reasoning, a variety of structural properties of this type of collective action.

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

PubMed

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

2017-03-01

Experiments in systems biology are generally supported by a computational model which quantitatively estimates the parameters of the system by finding the best fit to the experiment. Mathematical models have proved to be successful in reverse engineering the system. The data generated is interpreted to understand the dynamics of the underlying phenomena. The question we have sought to answer is that - is it possible to use an agent-based approach to re-engineer a biological process, making use of the available knowledge from experimental and modelling efforts? Can the bottom-up approach benefit from the top-down exercise so as to create an integrated modelling formalism for systems biology? We propose a modelling pipeline that learns from the data given by reverse engineering, and uses it for re-engineering the system, to carry out in-silico experiments. A mathematical model that quantitatively predicts co-expression of EGFR-HER2 receptors in activation and trafficking has been taken for this study. The pipeline architecture takes cues from the population model that gives the rates of biochemical reactions, to formulate knowledge-based rules for the particle model. Agent-based simulations using these rules, support the existing facts on EGFR-HER2 dynamics. We conclude that, re-engineering models, built using the results of reverse engineering, opens up the possibility of harnessing the power pack of data which now lies scattered in literature. Virtual experiments could then become more realistic when empowered with the findings of empirical cell biology and modelling studies. Implemented on the Agent Modelling Framework developed in-house. C ++ code templates available in Supplementary material . liz.csir@gmail.com. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Sedaxicenes: potential new antifungal ferrocene-based agents?

PubMed

Rubbiani, R; Blacque, O; Gasser, G

2016-04-21

Fungal infections are a group of diseases spread all over the world with an extremely high morbidity. Worryingly, although several pathogenic fungi were found to develop resistance towards traditional therapy, research towards the discovery of novel antimycotic agents is very limited. Considering the promising results obtained with the ferrocene-based drug candidates Ferroquine and Ferrocifen as antimalarial and anticancer drug candidates, respectively, we envisaged derivatizing the organic scaffold of a new broad-spectrum fungicide, namely sedaxane, with a ferrocenyl moiety in order to obtain new metal-based antifungal agents. The new ferrocenyl sedaxane derivatives called herein Sedaxicenes (, and ) were characterized using different analytical techniques and the structures were confirmed by X-ray crystallography. As expected for antimycotic agents, , and were found to have a low or even no toxicity towards human cells (IC50 > 100 μM). Interestingly, while the parent drug did not display any mycotoxicity (EC50 > 100 μM), complex was found to have some antifungal activity with an IC50 value of 43 μM under the same experimental conditions. In order to investigate the possible redox-mediated mode of action of , we synthesized the ruthenocene analogue of , namely . Ruthenocene is known to have a completely different electrochemical behaviour from ferrocene although both the compounds are isostructural. As anticipated, complex was found to induce an increase of the reactive oxygen species level in S. cerevisiae, contrary to its analogue and to the parent compound sedaxane.

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.

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

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.

Surface impact on nanoparticle-based magnetic resonance imaging contrast agents

PubMed Central

Zhang, Weizhong; Liu, Lin; Chen, Hongmin; Hu, Kai; Delahunty, Ian; Gao, Shi; Xie, Jin

2018-01-01

Magnetic resonance imaging (MRI) is one of the most widely used diagnostic tools in the clinic. To improve imaging quality, MRI contrast agents, which can modulate local T1 and T2 relaxation times, are often injected prior to or during MRI scans. However, clinically used contrast agents, including Gd3+-based chelates and iron oxide nanoparticles (IONPs), afford mediocre contrast abilities. To address this issue, there has been extensive research on developing alternative MRI contrast agents with superior r1 and r2 relaxivities. These efforts are facilitated by the fast progress in nanotechnology, which allows for preparation of magnetic nanoparticles (NPs) with varied size, shape, crystallinity, and composition. Studies suggest that surface coatings can also largely affect T1 and T2 relaxations and can be tailored in favor of a high r1 or r2. However, the surface impact of NPs has been less emphasized. Herein, we review recent progress on developing NP-based T1 and T2 contrast agents, with a focus on the surface impact. PMID:29721097

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

Agent-Centric Approach for Cybersecurity Decision-Support with Partial Observability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tipireddy, Ramakrishna; Chatterjee, Samrat; Paulson, Patrick R.

Generating automated cyber resilience policies for real-world settings is a challenging research problem that must account for uncertainties in system state over time and dynamics between attackers and defenders. In addition to understanding attacker and defender motives and tools, and identifying “relevant” system and attack data, it is also critical to develop rigorous mathematical formulations representing the defender’s decision-support problem under uncertainty. Game-theoretic approaches involving cyber resource allocation optimization with Markov decision processes (MDP) have been previously proposed in the literature. Moreover, advancements in reinforcement learning approaches have motivated the development of partially observable stochastic games (POSGs) in various multi-agentmore » problem domains with partial information. Recent advances in cyber-system state space modeling have also generated interest in potential applicability of POSGs for cybersecurity. However, as is the case in strategic card games such as poker, research challenges using game-theoretic approaches for practical cyber defense applications include: 1) solving for equilibrium and designing efficient algorithms for large-scale, general problems; 2) establishing mathematical guarantees that equilibrium exists; 3) handling possible existence of multiple equilibria; and 4) exploitation of opponent weaknesses. Inspired by advances in solving strategic card games while acknowledging practical challenges associated with the use of game-theoretic approaches in cyber settings, this paper proposes an agent-centric approach for cybersecurity decision-support with partial system state observability.« less

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.

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.

Model of mobile agents for sexual interactions networks

NASA Astrophysics Data System (ADS)

González, M. C.; Lind, P. G.; Herrmann, H. J.

2006-02-01

We present a novel model to simulate real social networks of complex interactions, based in a system of colliding particles (agents). The network is build by keeping track of the collisions and evolves in time with correlations which emerge due to the mobility of the agents. Therefore, statistical features are a consequence only of local collisions among its individual agents. Agent dynamics is realized by an event-driven algorithm of collisions where energy is gained as opposed to physical systems which have dissipation. The model reproduces empirical data from networks of sexual interactions, not previously obtained with other approaches.

Metareasoning and Social Evaluations in Cognitive Agents

NASA Astrophysics Data System (ADS)

Pinyol, Isaac; Sabater-Mir, Jordi

Reputation mechanisms have been recognized one of the key technologies when designing multi-agent systems. They are specially relevant in complex open environments, becoming a non-centralized mechanism to control interactions among agents. Cognitive agents tackling such complex societies must use reputation information not only for selecting partners to interact with, but also in metareasoning processes to change reasoning rules. This is the focus of this paper. We argue about the necessity to allow, as a cognitive systems designers, certain degree of freedom in the reasoning rules of the agents. We also describes cognitive approaches of agency that support this idea. Furthermore, taking as a base the computational reputation model Repage, and its integration in a BDI architecture, we use the previous ideas to specify metarules and processes to modify at run-time the reasoning paths of the agent. In concrete we propose a metarule to update the link between Repage and the belief base, and a metarule and a process to update an axiom incorporated in the belief logic of the agent. Regarding this last issue we also provide empirical results that show the evolution of agents that use it.

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.

Blood-pool contrast agent for pre-clinical computed tomography

NASA Astrophysics Data System (ADS)

Cruje, Charmainne; Tse, Justin J.; Holdsworth, David W.; Gillies, Elizabeth R.; Drangova, Maria

2017-03-01

Advances in nanotechnology have led to the development of blood-pool contrast agents for micro-computed tomography (micro-CT). Although long-circulating nanoparticle-based agents exist for micro-CT, they are predominantly based on iodine, which has a low atomic number. Micro-CT contrast increases when using elements with higher atomic numbers (i.e. lanthanides), particularly at higher energies. The purpose of our work was to develop and evaluate a lanthanide-based blood-pool contrast agent that is suitable for in vivo micro-CT. We synthesized a contrast agent in the form of polymer-encapsulated Gd nanoparticles and evaluated its stability in vitro. The synthesized nanoparticles were shown to have an average diameter of 127 +/- 6 nm, with good size dispersity. Particle size distribution - evaluated by dynamic light scattering over the period of two days - demonstrated no change in size of the contrast agent in water and saline. Additionally, our contrast agent was stable in a mouse serum mimic for up to 30 minutes. CT images of the synthesized contrast agent (containing 27 mg/mL of Gd) demonstrated an attenuation of over 1000 Hounsfield Units. This approach to synthesizing a Gd-based blood-pool contrast agent promises to enhance the capabilities of micro-CT imaging.

Developing framework for agent- based diabetes disease management system: user perspective.

PubMed

Mohammadzadeh, Niloofar; Safdari, Reza; Rahimi, Azin

2014-02-01

One of the characteristics of agents is mobility which makes them very suitable for remote electronic health and tele medicine. The aim of this study is developing a framework for agent based diabetes information management at national level through identifying required agents. The main tool is a questioner that is designed in three sections based on studying library resources, performance of major organizations in the field of diabetes in and out of the country and interviews with experts in the medical, health information management and software fields. Questionnaires based on Delphi methods were distributed among 20 experts. In order to design and identify agents required in health information management for the prevention and appropriate and rapid treatment of diabetes, the results were analyzed using SPSS 17 and Results were plotted with FREEPLANE mind map software. ACCESS TO DATA TECHNOLOGY IN PROPOSED FRAMEWORK IN ORDER OF PRIORITY IS: mobile (mean 1/80), SMS, EMAIL (mean 2/80), internet, web (mean 3/30), phone (mean 3/60), WIFI (mean 4/60). In delivering health care to diabetic patients, considering social and human aspects is essential. Having a systematic view for implementation of agent systems and paying attention to all aspects such as feedbacks, user acceptance, budget, motivation, hierarchy, useful standards, affordability of individuals, identifying barriers and opportunities and so on, are necessary.

Agent-based modeling of endotoxin-induced acute inflammatory response in human blood leukocytes.

PubMed

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

2010-02-18

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

Flip-angle based ratiometric approach for pulsed CEST-MRI pH imaging

NASA Astrophysics Data System (ADS)

Arena, Francesca; Irrera, Pietro; Consolino, Lorena; Colombo Serra, Sonia; Zaiss, Moritz; Longo, Dario Livio

2018-02-01

Several molecules have been exploited for developing MRI pH sensors based on the chemical exchange saturation transfer (CEST) technique. A ratiometric approach, based on the saturation of two exchanging pools at the same saturation power, or by varying the saturation power levels on the same pool, is usually needed to rule out the concentration term from the pH measurement. However, all these methods have been demonstrated by using a continuous wave saturation scheme that limits its translation to clinical scanners. This study shows a new ratiometric CEST-MRI pH-mapping approach based on a pulsed CEST saturation scheme for a radiographic contrast agent (iodixanol) possessing a single chemical exchange site. This approach is based on the ratio of the CEST contrast effects at two different flip angles combinations (180°/360° and 180°/720°), keeping constant the mean irradiation RF power (Bavg power). The proposed ratiometric approach index is concentration independent and it showed good pH sensitivity and accuracy in the physiological range between 6.0 and 7.4.

An agent-based method for simulating porous fluid-saturated structures with indistinguishable components

NASA Astrophysics Data System (ADS)

Kashani, Jamal; Pettet, Graeme John; Gu, YuanTong; Zhang, Lihai; Oloyede, Adekunle

2017-10-01

Single-phase porous materials contain multiple components that intermingle up to the ultramicroscopic level. Although the structures of the porous materials have been simulated with agent-based methods, the results of the available methods continue to provide patterns of distinguishable solid and fluid agents which do not represent materials with indistinguishable phases. This paper introduces a new agent (hybrid agent) and category of rules (intra-agent rule) that can be used to create emergent structures that would more accurately represent single-phase structures and materials. The novel hybrid agent carries the characteristics of system's elements and it is capable of changing within itself, while also responding to its neighbours as they also change. As an example, the hybrid agent under one-dimensional cellular automata formalism in a two-dimensional domain is used to generate patterns that demonstrate the striking morphological and characteristic similarities with the porous saturated single-phase structures where each agent of the ;structure; carries semi-permeability property and consists of both fluid and solid in space and at all times. We conclude that the ability of the hybrid agent to change locally provides an enhanced protocol to simulate complex porous structures such as biological tissues which could facilitate models for agent-based techniques and numerical methods.

Designing an architectural style for dynamic medical Cross-Organizational Workflow management system: an approach based on agents and web services.

PubMed

Bouzguenda, Lotfi; Turki, Manel

2014-04-01

This paper shows how the combined use of agent and web services technologies can help to design an architectural style for dynamic medical Cross-Organizational Workflow (COW) management system. Medical COW aims at supporting the collaboration between several autonomous and possibly heterogeneous medical processes, distributed over different organizations (Hospitals, Clinic or laboratories). Dynamic medical COW refers to occasional cooperation between these health organizations, free of structural constraints, where the medical partners involved and their number are not pre-defined. More precisely, this paper proposes a new architecture style based on agents and web services technologies to deal with two key coordination issues of dynamic COW: medical partners finding and negotiation between them. It also proposes how the proposed architecture for dynamic medical COW management system can connect to a multi-agent system coupling the Clinical Decision Support System (CDSS) with Computerized Prescriber Order Entry (CPOE). The idea is to assist the health professionals such as doctors, nurses and pharmacists with decision making tasks, as determining diagnosis or patient data analysis without stopping their clinical processes in order to act in a coherent way and to give care to the patient.

An Agent-Based Model of Evolving Community Flood Risk.

PubMed

Tonn, Gina L; Guikema, Seth D

2018-06-01

Although individual behavior plays a major role in community flood risk, traditional flood risk models generally do not capture information on how community policies and individual decisions impact the evolution of flood risk over time. The purpose of this study is to improve the understanding of the temporal aspects of flood risk through a combined analysis of the behavioral, engineering, and physical hazard aspects of flood risk. Additionally, the study aims to develop a new modeling approach for integrating behavior, policy, flood hazards, and engineering interventions. An agent-based model (ABM) is used to analyze the influence of flood protection measures, individual behavior, and the occurrence of floods and near-miss flood events on community flood risk. The ABM focuses on the following decisions and behaviors: dissemination of flood management information, installation of community flood protection, elevation of household mechanical equipment, and elevation of homes. The approach is place based, with a case study area in Fargo, North Dakota, but is focused on generalizable insights. Generally, community mitigation results in reduced future damage, and individual action, including mitigation and movement into and out of high-risk areas, can have a significant influence on community flood risk. The results of this study provide useful insights into the interplay between individual and community actions and how it affects the evolution of flood risk. This study lends insight into priorities for future work, including the development of more in-depth behavioral and decision rules at the individual and community level. © 2017 Society for Risk Analysis.

In vivo evaluation of neutron capture therapy effectivity using calcium phosphate-based nanoparticles as Gd-DTPA delivery agent.

PubMed

Dewi, Novriana; Mi, Peng; Yanagie, Hironobu; Sakurai, Yuriko; Morishita, Yasuyuki; Yanagawa, Masashi; Nakagawa, Takayuki; Shinohara, Atsuko; Matsukawa, Takehisa; Yokoyama, Kazuhito; Cabral, Horacio; Suzuki, Minoru; Sakurai, Yoshinori; Tanaka, Hiroki; Ono, Koji; Nishiyama, Nobuhiro; Kataoka, Kazunori; Takahashi, Hiroyuki

2016-04-01

A more immediate impact for therapeutic approaches of current clinical research efforts is of major interest, which might be obtained by developing a noninvasive radiation dose-escalation strategy, and neutron capture therapy represents one such novel approach. Furthermore, some recent researches on neutron capture therapy have focused on using gadolinium as an alternative or complementary for currently used boron, taking into account several advantages that gadolinium offers. Therefore, in this study, we carried out feasibility evaluation for both single and multiple injections of gadolinium-based MRI contrast agent incorporated in calcium phosphate nanoparticles as neutron capture therapy agent. In vivo evaluation was performed on colon carcinoma Col-26 tumor-bearing mice irradiated at nuclear reactor facility of Kyoto University Research Reactor Institute with average neutron fluence of 1.8 × 10(12) n/cm(2). Antitumor effectivity was evaluated based on tumor growth suppression assessed until 27 days after neutron irradiation, followed by histopathological analysis on tumor slice. The experimental results showed that the tumor growth of irradiated mice injected beforehand with Gd-DTPA-incorporating calcium phosphate-based nanoparticles was suppressed up to four times higher compared to the non-treated group, supported by the results of histopathological analysis. The results of antitumor effectivity observed on tumor-bearing mice after neutron irradiation indicated possible effectivity of gadolinium-based neutron capture therapy treatment.

Amino acid–based surfactants: New antimicrobial agents.

PubMed

Pinazo, A; Manresa, M A; Marques, A M; Bustelo, M; Espuny, M J; Pérez, L

2016-02-01

The rapid increase of drug resistant bacteria makes necessary the development of new antimicrobial agents. Synthetic amino acid-based surfactants constitute a promising alternative to conventional antimicrobial compounds given that they can be prepared from renewable raw materials. In this review, we discuss the structural features that promote antimicrobial activity of amino acid-based surfactants. Monocatenary, dicatenary and gemini surfactants that contain different amino acids on the polar head and show activity against bacteria are revised. The synthesis and basic physico-chemical properties have also been included.

Noncontraceptive use of contraceptive agents.

PubMed

Nickles, Monique Collier; Alderman, Elizabeth

2014-06-01

• On the basis of strong research evidence, there are many noncontraceptive advantages to use of hormonal contraceptive agents in adolescent girls. (3) (4)(5)(7)(10)(11)(12)(13)(14). • On the basis of research evidence and consensus, most of these agents are safe with minor adverse effects. (2)(3)(4)(5)(7)(10)(11)(12)(13)(14). • On the basis of research evidence and consensus, through application of evidence-based approaches and proper counseling, pediatricians can use various contraceptive agents to treat several medical conditions and to help alleviate many of the undesired symptoms and complications associated with menstrual periods. (2)(3)(4)(5)(7)(10)(11)(12)(13) (14). • On the basis of research evidence and consensus, these agents may be used in sexually active adolescents to simultaneously help prevent unintended adolescent pregnancies. (2)(3)(4)(5)(7)(10)(11)(12)(13)(14).

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

Physical agents used in the management of chronic pain by physical therapists.

PubMed

Allen, Roger J

2006-05-01

Evidence supporting the use of specific physical agents in the management of chronic pain conditions is not definitive; it is largely incomplete and sometimes contradictory. However, the use of agents in chronic pain management programs is common. Within the broad use of physical agents, they are rarely the sole modality of treatment. A 1995 American Physical Therapy Association position statement asserts that "Without documentation which justifies the necessity of the exclusive use of physical agents/modalities, the use of physical agents/modalities, in the absence of other skilled therapeutic or educational intervention, should not be considered physical therapy". Physical agents may serve as useful adjunctive modalities of pain relief or to enhance the effectiveness of other elements in therapy geared toward resolution of movement impairments and restoration of physical function. Given that a conclusive aggregate of findings is unlikely to exist for all permutations of patient conditions, combined with interacting therapeutic modalities, an evidence-based approach to pain management is not always possible or beneficial to the patient. In the face of inconclusive evidence, a theory-based approach may help determine if the therapeutic effect ofa given physical agent has the possibility of being a useful clinical tool in the context of treating a particular patient's mechanism of pain generation. Until controlled efficacy findings are definitive, careful individual patient response monitoring of thoughtful theoretical application of adjunctive physical agents may be a prudent approach to the management of chronic pain.

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

DTIC Science & Technology

2008-03-01

4. REPAST (Java, Python , C#, Open Source) ........28 5. MASON: Multi-Agent Modeling Language (Swarm Extension... Python , C#, Open Source) Repast (Recursive Porous Agent Simulation Toolkit) was designed for building agent-based models and simulations in the...Repast makes it easy for inexperienced users to build models by including a built-in simple model and provide interfaces through which menus and Python

Agent Reward Shaping for Alleviating Traffic Congestion

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Agogino, Adrian

2006-01-01

Traffic congestion problems provide a unique environment to study how multi-agent systems promote desired system level behavior. What is particularly interesting in this class of problems is that no individual action is intrinsically "bad" for the system but that combinations of actions among agents lead to undesirable outcomes, As a consequence, agents need to learn how to coordinate their actions with those of other agents, rather than learn a particular set of "good" actions. This problem is ubiquitous in various traffic problems, including selecting departure times for commuters, routes for airlines, and paths for data routers. In this paper we present a multi-agent approach to two traffic problems, where far each driver, an agent selects the most suitable action using reinforcement learning. The agent rewards are based on concepts from collectives and aim to provide the agents with rewards that are both easy to learn and that if learned, lead to good system level behavior. In the first problem, we study how agents learn the best departure times of drivers in a daily commuting environment and how following those departure times alleviates congestion. In the second problem, we study how agents learn to select desirable routes to improve traffic flow and minimize delays for. all drivers.. In both sets of experiments,. agents using collective-based rewards produced near optimal performance (93-96% of optimal) whereas agents using system rewards (63-68%) barely outperformed random action selection (62-64%) and agents using local rewards (48-72%) performed worse than random in some instances.

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

PubMed

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

2013-12-11

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

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

High performance cellular level agent-based simulation with FLAME for the GPU.

PubMed

Richmond, Paul; Walker, Dawn; Coakley, Simon; Romano, Daniela

2010-05-01

Driven by the availability of experimental data and ability to simulate a biological scale which is of immediate interest, the cellular scale is fast emerging as an ideal candidate for middle-out modelling. As with 'bottom-up' simulation approaches, cellular level simulations demand a high degree of computational power, which in large-scale simulations can only be achieved through parallel computing. The flexible large-scale agent modelling environment (FLAME) is a template driven framework for agent-based modelling (ABM) on parallel architectures ideally suited to the simulation of cellular systems. It is available for both high performance computing clusters (www.flame.ac.uk) and GPU hardware (www.flamegpu.com) and uses a formal specification technique that acts as a universal modelling format. This not only creates an abstraction from the underlying hardware architectures, but avoids the steep learning curve associated with programming them. In benchmarking tests and simulations of advanced cellular systems, FLAME GPU has reported massive improvement in performance over more traditional ABM frameworks. This allows the time spent in the development and testing stages of modelling to be drastically reduced and creates the possibility of real-time visualisation for simple visual face-validation.

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.

Integration agent-based models and GIS as a virtual urban dynamic laboratory

NASA Astrophysics Data System (ADS)

Chen, Peng; Liu, Miaolong

2007-06-01

Based on the Agent-based Model and spatial data model, a tight-coupling integrating method of GIS and Agent-based Model (ABM) is to be discussed in this paper. 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 such as urban dynamic. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, the agent-based model and spatial data model are discussed, and then the relationships affecting spatial data model and agent-based process models interaction. After that, a realistic crowd flow simulation experiment is presented. Using some tools provided by general GIS systems and a few specific programming languages, a new software system integrating GIS and MAS as a virtual laboratory applicable for simulating pedestrian flows in a crowd activity centre has been developed successfully. Under the environment supported by the software system, as an applicable case, a dynamic evolution process of the pedestrian's flows (dispersed process for the spectators) in a crowds' activity center - The Shanghai Stadium has been simulated successfully. At the end of the paper, some new research problems have been pointed out for the future.

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.

Phenomenological modelling of self-healing polymers based on integrated healing agents

NASA Astrophysics Data System (ADS)

Mergheim, Julia; Steinmann, Paul

2013-09-01

The present contribution introduces a phenomenological model for self-healing polymers. Self-healing polymers are a promising class of materials which mimic nature by their capability to autonomously heal micro-cracks. This self-healing is accomplished by the integration of microcapsules containing a healing agent and a dispersed catalyst into the matrix material. Propagating microcracks may then break the capsules which releases the healing agent into the microcracks where it polymerizes with the catalyst, closes the crack and 'heals' the material. The present modelling approach treats these processes at the macroscopic scale, the microscopic details of crack propagation and healing are thus described by means of continuous damage and healing variables. The formulation of the healing model accounts for the fact that healing is directly associated with the curing process of healing agent and catalyst. The model is implemented and its capabilities are studied by means of numerical examples.

Children's Agentive Orientations in Play-Based and Academically Focused Preschools in Hong Kong

ERIC Educational Resources Information Center

Cheng Pui-Wah, Doris; Reunamo, Jyrki; Cooper, Paul; Liu, Karen; Vong, Keang-ieng Peggy

2015-01-01

The article describes a comparative case study on children's agentive orientations in two Hong Kong preschools, one is play-based and the other is academically focused. Agentive orientations were measured using Reunamo's interview tool, which focuses on children's uses of accommodative and agentive orientations in everyday situations. The findings…

Coordination between Generation and Transmission Maintenance Scheduling by Means of Multi-agent Technique

NASA Astrophysics Data System (ADS)

Nagata, Takeshi; Tao, Yasuhiro; Utatani, Masahiro; Sasaki, Hiroshi; Fujita, Hideki

This paper proposes a multi-agent approach to maintenance scheduling in restructured power systems. The restructuring of electric power industry has resulted in market-based approaches for unbundling a multitude of service provided by self-interested entities such as power generating companies (GENCOs), transmission providers (TRANSCOs) and distribution companies (DISCOs). The Independent System Operator (ISO) is responsible for the security of the system operation. The schedule submitted to ISO by GENCOs and TRANSCOs should satisfy security and reliability constraints. The proposed method consists of several GENCO Agents (GAGs), TARNSCO Agents (TAGs) and a ISO Agent(IAG). The IAG’s role in maintenance scheduling is limited to ensuring that the submitted schedules do not cause transmission congestion or endanger the system reliability. From the simulation results, it can be seen the proposed multi-agent approach could coordinate between generation and transmission maintenance schedules.

Multi-agent system as a new approach to effective chronic heart failure management: key considerations.

PubMed

Mohammadzadeh, Niloofar; Safdari, Reza; Rahimi, Azin

2013-09-01

Given the importance of the follow-up of chronic heart failure (CHF) patients to reduce common causes of re-admission and deterioration of their status that lead to imposing spiritual and physical costs on patients and society, modern technology tools should be used to the best advantage. The aim of this article is to explain key points which should be considered in designing an appropriate multi-agent system to improve CHF management. In this literature review articles were searched with keywords like multi-agent system, heart failure, chronic disease management in Science Direct, Google Scholar and PubMed databases without regard to the year of publications. Agents are an innovation in the field of artificial intelligence. Because agents are capable of solving complex and dynamic health problems, to take full advantage of e-Health, the healthcare system must take steps to make use of this technology. Key factors in CHF management through a multi-agent system approach must be considered such as organization, confidentiality in general aspects and design and architecture points in specific aspects. Note that use of agent systems only with a technical view is associated with many problems. Hence, in delivering healthcare to CHF patients, considering social and human aspects is essential. It is obvious that identifying and resolving technical and non-technical challenges is vital in the successful implementation of this technology.

Web based listing of agents associated with new onset work-related asthma.

PubMed

Rosenman, K D; Beckett, W S

2015-05-01

Work-related asthma is common and yet remains a challenge to diagnose. Access to a listing of agents associated with work-related asthma has been suggested as useful in assisting in the diagnosis. The Association of Occupational and Environmental Clinics (AOEC) developed criteria that were used to review the peer-reviewed medical literature published in English. Based on this review, substances were designated either as a sensitizing agent or an irritant. The reviews were conducted by a board certified internist/pulmonologist/occupational medicine specialist from 2002 to 2007 and a board certified internist/occupational medicine physician from 2008- date. All reviews were then reviewed by the nine member AOEC board of directors. The original list of agents associated with new onset work-related asthma was derived from the tables of a text book on work-related asthma. After 13 years of review, there are 327 substances designated as asthma agents on the AOEC list; 173 (52.9%) coded as sensitizers, 35 (10.7%) as generally recognized as an asthma causing agent, four (1.2%) as irritants, two (0.6%) as both a sensitizer and an irritant and 113(34.6%) agents that still need to be reviewed. The AOEC has developed a readily available web based listing of agents associated with new onset work-related asthma in adults. The listing is based on peer-reviewed criteria. The listing is updated twice a year. Regular review of the peer-reviewed medical literature is conducted to determine whether new substances should be added to the list. Clinicians should find the list useful when considering the diagnosis of work-related asthma. Copyright © 2015 Elsevier Ltd. All rights reserved.

X-ray spatial frequency heterodyne imaging of protein-based nanobubble contrast agents

PubMed Central

Rand, Danielle; Uchida, Masaki; Douglas, Trevor; Rose-Petruck, Christoph

2014-01-01

Spatial Frequency Heterodyne Imaging (SFHI) is a novel x-ray scatter imaging technique that utilizes nanoparticle contrast agents. The enhanced sensitivity of this new technique relative to traditional absorption-based x-ray radiography makes it promising for applications in biomedical and materials imaging. Although previous studies on SFHI have utilized only metal nanoparticle contrast agents, we show that nanomaterials with a much lower electron density are also suitable. We prepared protein-based “nanobubble” contrast agents that are comprised of protein cage architectures filled with gas. Results show that these nanobubbles provide contrast in SFHI comparable to that of gold nanoparticles of similar size. PMID:25321797

Use of agents to implement an integrated computing environment

NASA Technical Reports Server (NTRS)

Hale, Mark A.; Craig, James I.

1995-01-01

Integrated Product and Process Development (IPPD) embodies the simultaneous application to both system and quality engineering methods throughout an iterative design process. The use of IPPD results in the time-conscious, cost-saving development of engineering systems. To implement IPPD, a Decision-Based Design perspective is encapsulated in an approach that focuses on the role of the human designer in product development. The approach has two parts and is outlined in this paper. First, an architecture, called DREAMS, is being developed that facilitates design from a decision-based perspective. Second, a supporting computing infrastructure, called IMAGE, is being designed. Agents are used to implement the overall infrastructure on the computer. Successful agent utilization requires that they be made of three components: the resource, the model, and the wrap. Current work is focused on the development of generalized agent schemes and associated demonstration projects. When in place, the technology independent computing infrastructure will aid the designer in systematically generating knowledge used to facilitate decision-making.

The evolution of gadolinium based contrast agents: from single-modality to multi-modality

NASA Astrophysics Data System (ADS)

Zhang, Li; Liu, Ruiqing; Peng, Hui; Li, Penghui; Xu, Zushun; Whittaker, Andrew K.

2016-05-01

Gadolinium-based contrast agents are extensively used as magnetic resonance imaging (MRI) contrast agents due to their outstanding signal enhancement and ease of chemical modification. However, it is increasingly recognized that information obtained from single modal molecular imaging cannot satisfy the higher requirements on the efficiency and accuracy for clinical diagnosis and medical research, due to its limitation and default rooted in single molecular imaging technique itself. To compensate for the deficiencies of single function magnetic resonance imaging contrast agents, the combination of multi-modality imaging has turned to be the research hotpot in recent years. This review presents an overview on the recent developments of the functionalization of gadolinium-based contrast agents, and their application in biomedicine applications.

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.

Rapid Catalyst Capture Enables Metal-Free para-Hydrogen-Based Hyperpolarized Contrast Agents.

PubMed

Barskiy, Danila A; Ke, Lucia A; Li, Xingyang; Stevenson, Vincent; Widarman, Nevin; Zhang, Hao; Truxal, Ashley; Pines, Alexander

2018-05-10

Hyperpolarization techniques based on the use of para-hydrogen provide orders of magnitude signal enhancement for magnetic resonance spectroscopy and imaging. The main drawback limiting widespread applicability of para-hydrogen-based techniques in biomedicine is the presence of organometallic compounds (the polarization transfer catalysts) in solution with hyperpolarized contrast agents. These catalysts are typically complexes of platinum-group metals, and their administration in vivo should be avoided. Herein, we show how extraction of a hyperpolarized compound from an organic phase to an aqueous phase combined with a rapid (less than 10 s) Ir-based catalyst capture by metal scavenging agents can produce pure para-hydrogen-based hyperpolarized contrast agents, as demonstrated by high-resolution nuclear magnetic resonance (NMR) spectroscopy and inductively coupled plasma atomic emission spectroscopy (ICP-AES). The presented methodology enables fast and efficient means of producing pure hyperpolarized aqueous solutions for biomedical and other uses.

School-Based Decision Making: A Principal-Agent Perspective.

ERIC Educational Resources Information Center

Ferris, James M.

1992-01-01

A principal-agent framework is used to examine potential gains in educational performance and potential threats to public accountability that school-based decision-making proposals pose. Analysis underscores the need to tailor the design of decentralized decision making to the sources of poor educational performance and threats to school…

EVA: Collaborative Distributed Learning Environment Based in Agents.

ERIC Educational Resources Information Center

Sheremetov, Leonid; Tellez, Rolando Quintero

In this paper, a Web-based learning environment developed within the project called Virtual Learning Spaces (EVA, in Spanish) is presented. The environment is composed of knowledge, collaboration, consulting, experimentation, and personal spaces as a collection of agents and conventional software components working over the knowledge domains. All…

A Multiscale Agent-Based in silico Model of Liver Fibrosis Progression

PubMed Central

Dutta-Moscato, Joyeeta; Solovyev, Alexey; Mi, Qi; Nishikawa, Taichiro; Soto-Gutierrez, Alejandro; Fox, Ira J.; Vodovotz, Yoram

2014-01-01

Chronic hepatic inflammation involves a complex interplay of inflammatory and mechanical influences, ultimately manifesting in a characteristic histopathology of liver fibrosis. We created an agent-based model (ABM) of liver tissue in order to computationally examine the consequence of liver inflammation. Our liver fibrosis ABM (LFABM) is comprised of literature-derived rules describing molecular and histopathological aspects of inflammation and fibrosis in a section of chemically injured liver. Hepatocytes are modeled as agents within hexagonal lobules. Injury triggers an inflammatory reaction, which leads to activation of local Kupffer cells and recruitment of monocytes from circulation. Portal fibroblasts and hepatic stellate cells are activated locally by the products of inflammation. The various agents in the simulation are regulated by above-threshold concentrations of pro- and anti-inflammatory cytokines and damage-associated molecular pattern molecules. The simulation progresses from chronic inflammation to collagen deposition, exhibiting periportal fibrosis followed by bridging fibrosis, and culminating in disruption of the regular lobular structure. The ABM exhibited key histopathological features observed in liver sections from rats treated with carbon tetrachloride (CCl4). An in silico “tension test” for the hepatic lobules predicted an overall increase in tissue stiffness, in line with clinical elastography literature and published studies in CCl4-treated rats. Therapy simulations suggested differential anti-fibrotic effects of neutralizing tumor necrosis factor alpha vs. enhancing M2 Kupffer cells. We conclude that a computational model of liver inflammation on a structural skeleton of physical forces can recapitulate key histopathological and macroscopic properties of CCl4-injured liver. This multiscale approach linking molecular and chemomechanical stimuli enables a model that could be used to gain translationally relevant insights into liver

Interfacial Stacks of Polymeric Nanofilms on Soft Biological Surfaces that Release Multiple Agents.

PubMed

Herron, Maggie; Schurr, Michael J; Murphy, Christopher J; McAnulty, Jonathan F; Czuprynski, Charles J; Abbott, Nicholas L

2016-10-03

We report a general and facile method that permits the transfer (stacking) of multiple independently fabricated and nanoscopically thin polymeric films, each containing a distinct bioactive agent, onto soft biomedically relevant surfaces (e.g., collagen-based wound dressings). By using polyelectrolyte multilayer films (PEMs) formed from poly(allyl amine hydrochloride) and poly(acrylic acid) as representative polymeric nanofilms and micrometer-thick water-soluble poly(vinyl alcohol) sacrificial films to stack the PEMs, we demonstrate that it is possible to create stacked polymeric constructs containing multiple bioactive agents (e.g., antimicrobial and antibiofilm agents) on soft and chemically complex surfaces onto which PEMs cannot be routinely transferred by stamping. We illustrate the characteristics and merits of the approach by fabricating stacks of Ga 3+ (antibiofilm agent)- and Ag + (antimicrobial agent)-loaded PEMs as prototypical examples of agent-containing PEMs and demonstrate that the stacked PEMs incorporate precise loadings of the agents and provide flexibility in terms of tuning release rates. Specifically, we show that simultaneous release of Ga 3+ and Ag + from the stacked PEMs on collagen-based wound dressings can lead to synergistic effects on bacteria, killing and dispersing biofilms formed by Pseudomonas aeruginosa (two strains: ATCC 27853 and MPAO1) at sufficiently low loadings of agents such that cytotoxic effects on mammalian cells are avoided. The approach is general (a wide range of bioactive agents other than Ga 3+ and Ag + can be incorporated into PEMs), and the modular nature of the approach potentially allows end-user functionalization of soft biological surfaces for programmed release of multiple bioactive agents.

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).…

Agent-Based Negotiation in Uncertain Environments

NASA Astrophysics Data System (ADS)

Debenham, John; Sierra, Carles

An agent aims to secure his projected needs by attempting to build a set of (business) relationships with other agents. A relationship is built by exchanging private information, and is characterised by its intimacy — degree of closeness — and balance — degree of fairness. Each argumentative interaction between two agents then has two goals: to satisfy some immediate need, and to do so in a way that develops the relationship in a desired direction. An agent's desire to develop each relationship in a particular way then places constraints on the argumentative utterances. The form of negotiation described is argumentative interaction constrained by a desire to develop such relationships.

Novel agents and approaches for stem cell mobilization in normal donors and patients.

PubMed

Bakanay, Ş M; Demirer, T

2012-09-01

In spite of the safety and efficiency of the classical mobilization protocols, recombinant human G-CSF±chemotherapy, there is still a considerable amount of mobilization failures (10-30%), which warrant novel agents and approaches both in an autologous and an allogeneic transplant setting. Attempts to improve CD34+ yields by using several cytokines and growth factors as adjuncts to G-CSF could not change the standard approaches during the last decade, either because of inefficiency or the adverse events encountered with these agents. As a long-acting G-CSF analog, pegfilgrastim has the advantages of an earlier start of apheresis, reduction in the number of apheresis procedures as well as a reduced number of injections as compared with unconjugated G-CSF. However, dosing and cost-effectiveness especially in cytokine-only mobilizations require further investigation. As interactions between hematopoietic stem cells and the BM microenvironment are better understood, new molecules targeting these interactions are emerging. Plerixafor, which started its journey as an anti-HIV drug, recently ended up being a popular stem cell mobilizer with the ability of rapid mobilization and gained approval as an adjunct to G-CSF for poor mobilizers. At present, it is challenging to search for the best approach by using the available drugs with appropriate timing to provide sufficient CD34+ yield after an initial mobilization attempt, and in a cost-effective manner thereby avoiding further mobilization attempts and exposure to chemotherapy. Approaches not only for increasing stem cell yield, but also aiming to improve the quality of graft content and the associated transplantation outcomes are promising areas of research.

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

Adhesion strength of norbornene-based self-healing agents to an amine-cured epoxy

NASA Astrophysics Data System (ADS)

Huang, Guang Chun; Lee, Jong Keun; Kessler, Michael R.; Yoon, Sungho

2009-07-01

Self-healing is triggered by crack propagation through embedded microcapsules in an epoxy matrix, which then release the liquid healing agent into the crack plane. Subsequent exposure of the healing agent to the chemical catalyst initiates ring-opening metathesis polymerization (ROMP) and bonding of the crack faces. In order to improve self-healing functionality, it is necessary to enhance adhesion of polymerized healing agent within the crack to the matrix resin. In this study, shear bond strength between different norbornene-based healing agents and an amine-cured epoxy resin was evaluated using the single lap shear test method (ASTM D3163, modified). The healing agents tested include endodicyclopentadiene (endo-DCPD), 5-ethylidene-2-norbornene (ENB) and DCPD/ENB blends. 5-Norbornene-2-methanol (NBM) was used as an adhesion promoter, containing hydroxyl groups to form hydrogen bonds with the amine-cured epoxy. A custom synthesized norbornene-based crosslinking agent was also added to improve adhesion for ENB by increasing the crosslinking density of the adhesive after ROMP. The healing agents were polymerized with varying loadings of the 1st generation Grubbs' catalyst at different reaction times and temperatures.

Building occupancy simulation and data assimilation using a graph-based agent-oriented model

NASA Astrophysics Data System (ADS)

Rai, Sanish; Hu, Xiaolin

2018-07-01

Building occupancy simulation and estimation simulates the dynamics of occupants and estimates their real-time spatial distribution in a building. It requires a simulation model and an algorithm for data assimilation that assimilates real-time sensor data into the simulation model. Existing building occupancy simulation models include agent-based models and graph-based models. The agent-based models suffer high computation cost for simulating large numbers of occupants, and graph-based models overlook the heterogeneity and detailed behaviors of individuals. Recognizing the limitations of existing models, this paper presents a new graph-based agent-oriented model which can efficiently simulate large numbers of occupants in various kinds of building structures. To support real-time occupancy dynamics estimation, a data assimilation framework based on Sequential Monte Carlo Methods is also developed and applied to the graph-based agent-oriented model to assimilate real-time sensor data. Experimental results show the effectiveness of the developed model and the data assimilation framework. The major contributions of this work are to provide an efficient model for building occupancy simulation that can accommodate large numbers of occupants and an effective data assimilation framework that can provide real-time estimations of building occupancy from sensor data.

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

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.

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.

An Agent-Based Dynamic Model for Analysis of Distributed Space Exploration Architectures

NASA Astrophysics Data System (ADS)

Sindiy, Oleg V.; DeLaurentis, Daniel A.; Stein, William B.

2009-07-01

A range of complex challenges, but also potentially unique rewards, underlie the development of exploration architectures that use a distributed, dynamic network of resources across the solar system. From a methodological perspective, the prime challenge is to systematically model the evolution (and quantify comparative performance) of such architectures, under uncertainty, to effectively direct further study of specialized trajectories, spacecraft technologies, concept of operations, and resource allocation. A process model for System-of-Systems Engineering is used to define time-varying performance measures for comparative architecture analysis and identification of distinguishing patterns among interoperating systems. Agent-based modeling serves as the means to create a discrete-time simulation that generates dynamics for the study of architecture evolution. A Solar System Mobility Network proof-of-concept problem is introduced representing a set of longer-term, distributed exploration architectures. Options within this set revolve around deployment of human and robotic exploration and infrastructure assets, their organization, interoperability, and evolution, i.e., a system-of-systems. Agent-based simulations quantify relative payoffs for a fully distributed architecture (which can be significant over the long term), the latency period before they are manifest, and the up-front investment (which can be substantial compared to alternatives). Verification and sensitivity results provide further insight on development paths and indicate that the framework and simulation modeling approach may be useful in architectural design of other space exploration mass, energy, and information exchange settings.

Calibrating emergent phenomena in stock markets with agent based models

PubMed Central

Sornette, Didier

2018-01-01

Since the 2008 financial crisis, agent-based models (ABMs), which account for out-of-equilibrium dynamics, heterogeneous preferences, time horizons and strategies, have often been envisioned as the new frontier that could revolutionise and displace the more standard models and tools in economics. However, their adoption and generalisation is drastically hindered by the absence of general reliable operational calibration methods. Here, we start with a different calibration angle that qualifies an ABM for its ability to achieve abnormal trading performance with respect to the buy-and-hold strategy when fed with real financial data. Starting from the common definition of standard minority and majority agents with binary strategies, we prove their equivalence to optimal decision trees. This efficient representation allows us to exhaustively test all meaningful single agent models for their potential anomalous investment performance, which we apply to the NASDAQ Composite index over the last 20 years. We uncover large significant predictive power, with anomalous Sharpe ratio and directional accuracy, in particular during the dotcom bubble and crash and the 2008 financial crisis. A principal component analysis reveals transient convergence between the anomalous minority and majority models. A novel combination of the optimal single-agent models of both classes into a two-agents model leads to remarkable superior investment performance, especially during the periods of bubbles and crashes. Our design opens the field of ABMs to construct novel types of advanced warning systems of market crises, based on the emergent collective intelligence of ABMs built on carefully designed optimal decision trees that can be reversed engineered from real financial data. PMID:29499049

Calibrating emergent phenomena in stock markets with agent based models.

PubMed

Fievet, Lucas; Sornette, Didier

2018-01-01

Since the 2008 financial crisis, agent-based models (ABMs), which account for out-of-equilibrium dynamics, heterogeneous preferences, time horizons and strategies, have often been envisioned as the new frontier that could revolutionise and displace the more standard models and tools in economics. However, their adoption and generalisation is drastically hindered by the absence of general reliable operational calibration methods. Here, we start with a different calibration angle that qualifies an ABM for its ability to achieve abnormal trading performance with respect to the buy-and-hold strategy when fed with real financial data. Starting from the common definition of standard minority and majority agents with binary strategies, we prove their equivalence to optimal decision trees. This efficient representation allows us to exhaustively test all meaningful single agent models for their potential anomalous investment performance, which we apply to the NASDAQ Composite index over the last 20 years. We uncover large significant predictive power, with anomalous Sharpe ratio and directional accuracy, in particular during the dotcom bubble and crash and the 2008 financial crisis. A principal component analysis reveals transient convergence between the anomalous minority and majority models. A novel combination of the optimal single-agent models of both classes into a two-agents model leads to remarkable superior investment performance, especially during the periods of bubbles and crashes. Our design opens the field of ABMs to construct novel types of advanced warning systems of market crises, based on the emergent collective intelligence of ABMs built on carefully designed optimal decision trees that can be reversed engineered from real financial data.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paul M. Torrens; Atsushi Nara; Xun Li

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-usedmore » 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.« less

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…

An Agent Based Collaborative Simplification of 3D Mesh Model

NASA Astrophysics Data System (ADS)

Wang, Li-Rong; Yu, Bo; Hagiwara, Ichiro

Large-volume mesh model faces the challenge in fast rendering and transmission by Internet. The current mesh models obtained by using three-dimensional (3D) scanning technology are usually very large in data volume. This paper develops a mobile agent based collaborative environment on the development platform of mobile-C. Communication among distributed agents includes grasping image of visualized mesh model, annotation to grasped image and instant message. Remote and collaborative simplification can be efficiently conducted by Internet.

Reducing Traffic Congestions by Introducing CACC-Vehicles on a Multi-Lane Highway Using Agent-Based Approach

NASA Technical Reports Server (NTRS)

Arnaout, Georges M.; Bowling, Shannon R.

2011-01-01

Traffic congestion is an ongoing problem of great interest to researchers from different areas in academia. With the emerging technology for inter-vehicle communication, vehicles have the ability to exchange information with predecessors by wireless communication. In this paper, we present an agent-based model of traffic congestion and examine the impact of having CACC (Cooperative Adaptive Cruise Control) embedded vehicle(s) on a highway system consisting of 4 traffic lanes without overtaking. In our model, CACC vehicles adapt their acceleration/deceleration according to vehicle-to-vehicle inter-communication. We analyze the average speed of the cars, the shockwaves, and the evolution of traffic congestion throughout the lifecycle of the model. The study identifies how CACC vehicles affect the dynamics of traffic flow on a complex network and reduce the oscillatory behavior (stop and go) resulting from the acceleration/deceleration of the vehicles.

Designing an Agent-Based Model for Childhood Obesity Interventions: A Case Study of ChildObesity180.

PubMed

Hennessy, Erin; Ornstein, Joseph T; Economos, Christina D; Herzog, Julia Bloom; Lynskey, Vanessa; Coffield, Edward; Hammond, Ross A

2016-01-07

Complex systems modeling can provide useful insights when designing and anticipating the impact of public health interventions. We developed an agent-based, or individual-based, computation model (ABM) to aid in evaluating and refining implementation of behavior change interventions designed to increase physical activity and healthy eating and reduce unnecessary weight gain among school-aged children. The potential benefits of applying an ABM approach include estimating outcomes despite data gaps, anticipating impact among different populations or scenarios, and exploring how to expand or modify an intervention. The practical challenges inherent in implementing such an approach include data resources, data availability, and the skills and knowledge of ABM among the public health obesity intervention community. The aim of this article was to provide a step-by-step guide on how to develop an ABM to evaluate multifaceted interventions on childhood obesity prevention in multiple settings. We used data from 2 obesity prevention initiatives and public-use resources. The details and goals of the interventions, overview of the model design process, and generalizability of this approach for future interventions is discussed.

Verifying Multi-Agent Systems via Unbounded Model Checking

NASA Technical Reports Server (NTRS)

Kacprzak, M.; Lomuscio, A.; Lasica, T.; Penczek, W.; Szreter, M.

2004-01-01

We present an approach to the problem of verification of epistemic properties in multi-agent systems by means of symbolic model checking. In particular, it is shown how to extend the technique of unbounded model checking from a purely temporal setting to a temporal-epistemic one. In order to achieve this, we base our discussion on interpreted systems semantics, a popular semantics used in multi-agent systems literature. We give details of the technique and show how it can be applied to the well known train, gate and controller problem. Keywords: model checking, unbounded model checking, multi-agent systems

Research of negotiation in network trade system based on multi-agent

NASA Astrophysics Data System (ADS)

Cai, Jun; Wang, Guozheng; Wu, Haiyan

2009-07-01

A construction and implementation technology of network trade based on multi-agent is described in this paper. First, we researched the technology of multi-agent, then we discussed the consumer's behaviors and the negotiation between purchaser and bargainer which emerges in the traditional business mode and analysed the key technology to implement the network trade system. Finally, we implement the system.

An Agent-Based Modeling Framework and Application for the Generic Nuclear Fuel Cycle

NASA Astrophysics Data System (ADS)

Gidden, Matthew J.

Key components of a novel methodology and implementation of an agent-based, dynamic nuclear fuel cycle simulator, Cyclus , are presented. The nuclear fuel cycle is a complex, physics-dependent supply chain. To date, existing dynamic simulators have not treated constrained fuel supply, time-dependent, isotopic-quality based demand, or fuel fungibility particularly well. Utilizing an agent-based methodology that incorporates sophisticated graph theory and operations research techniques can overcome these deficiencies. This work describes a simulation kernel and agents that interact with it, highlighting the Dynamic Resource Exchange (DRE), the supply-demand framework at the heart of the kernel. The key agent-DRE interaction mechanisms are described, which enable complex entity interaction through the use of physics and socio-economic models. The translation of an exchange instance to a variant of the Multicommodity Transportation Problem, which can be solved feasibly or optimally, follows. An extensive investigation of solution performance and fidelity is then presented. Finally, recommendations for future users of Cyclus and the DRE are provided.

Multi-Agent System as a New Approach to Effective Chronic Heart Failure Management: Key Considerations