Agent Based Modeling Of Social Conflict
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Author | : Carlos M. Lemos |
Publisher | : Springer |
Total Pages | : 132 |
Release | : 2017-10-24 |
Genre | : Social Science |
ISBN | : 3319670506 |
This Brief revisits and extends Epstein’s classical agent-based model of civil violence by considering important mechanisms suggested by social conflict theories. Among them are: relative deprivation as generator of hardship, generalized vanishing of the risk perception (‘massive fear loss’) when the uprisings surpass a certain threshold, endogenous legitimacy feedback, and network influence effects represented by the mechanism of dispositional contagion. The model is explored in a set of computer experiments designed to provide insight on how mechanisms lead to increased complexity of the solutions. The results of the simulations are compared with statistical analyses of estimated size, duration and recurrence of large demonstrations and riots for eight African countries affected by the “Arab Spring,” based on the Social Conflict Analysis Database. It is shown that the extensions to Epstein’s model proposed herein lead to increased “generative capacity” of the agent-based model (i.e. a richer set of meaningful qualitative behaviors) as well the identification of key mechanisms and associated parameters with tipping points. The use of quantitative information (international indicators and statistical analyses of conflict events) allows the assessment of the plausibility of input parameter values and simulated results, and thus a better understanding of the model’s strengths and limitations. The contributions of the present work for understanding how mechanisms of large scale conflict lead to complexbehavior include a new form of the estimated arrest probability, a simple representation of political vs economic deprivation with a parameter which controls the `sensitivity' to value, endogenous legitimacy feedback, and the effect of network influences (due to small groups and “activists”). In addition, the analysis of the Social Conflict Analysis Database provided a quantitative description of the impact of the “Arab Spring” in several countries focused on complexity issues such as peaceful vs violent, spontaneous vs organized, and patterns of size, duration and recurrence of conflict events in this recent and important large-scale conflict process. This book will appeal to students and researchers working in these computational social science subfields.
Author | : Uri Wilensky |
Publisher | : MIT Press |
Total Pages | : 505 |
Release | : 2015-04-03 |
Genre | : Computers |
ISBN | : 0262731894 |
A comprehensive and hands-on introduction to the core concepts, methods, and applications of agent-based modeling, including detailed NetLogo examples. The advent of widespread fast computing has enabled us to work on more complex problems and to build and analyze more complex models. This book provides an introduction to one of the primary methodologies for research in this new field of knowledge. Agent-based modeling (ABM) offers a new way of doing science: by conducting computer-based experiments. ABM is applicable to complex systems embedded in natural, social, and engineered contexts, across domains that range from engineering to ecology. An Introduction to Agent-Based Modeling offers a comprehensive description of the core concepts, methods, and applications of ABM. Its hands-on approach—with hundreds of examples and exercises using NetLogo—enables readers to begin constructing models immediately, regardless of experience or discipline. The book first describes the nature and rationale of agent-based modeling, then presents the methodology for designing and building ABMs, and finally discusses how to utilize ABMs to answer complex questions. Features in each chapter include step-by-step guides to developing models in the main text; text boxes with additional information and concepts; end-of-chapter explorations; and references and lists of relevant reading. There is also an accompanying website with all the models and code.
Author | : Alexander Smajgl |
Publisher | : Springer Science & Business Media |
Total Pages | : 254 |
Release | : 2013-09-12 |
Genre | : Mathematics |
ISBN | : 1461461340 |
This instructional book showcases techniques to parameterise human agents in empirical agent-based models (ABM). In doing so, it provides a timely overview of key ABM methodologies and the most innovative approaches through a variety of empirical applications. It features cutting-edge research from leading academics and practitioners, and will provide a guide for characterising and parameterising human agents in empirical ABM. In order to facilitate learning, this text shares the valuable experiences of other modellers in particular modelling situations. Very little has been published in the area of empirical ABM, and this contributed volume will appeal to graduate-level students and researchers studying simulation modeling in economics, sociology, ecology, and trans-disciplinary studies, such as topics related to sustainability. In a similar vein to the instruction found in a cookbook, this text provides the empirical modeller with a set of 'recipes' ready to be implemented. Agent-based modeling (ABM) is a powerful, simulation-modeling technique that has seen a dramatic increase in real-world applications in recent years. In ABM, a system is modeled as a collection of autonomous decision-making entities called “agents.” Each agent individually assesses its situation and makes decisions on the basis of a set of rules. Agents may execute various behaviors appropriate for the system they represent—for example, producing, consuming, or selling. ABM is increasingly used for simulating real-world systems, such as natural resource use, transportation, public health, and conflict. Decision makers increasingly demand support that covers a multitude of indicators that can be effectively addressed using ABM. This is especially the case in situations where human behavior is identified as a critical element. As a result, ABM will only continue its rapid growth. This is the first volume in a series of books that aims to contribute to a cultural change in the community of empirical agent-based modelling. This series will bring together representational experiences and solutions in empirical agent-based modelling. Creating a platform to exchange such experiences allows comparison of solutions and facilitates learning in the empirical agent-based modelling community. Ultimately, the community requires such exchange and learning to test approaches and, thereby, to develop a robust set of techniques within the domain of empirical agent-based modelling. Based on robust and defendable methods, agent-based modelling will become a critical tool for research agencies, decision making and decision supporting agencies, and funding agencies. This series will contribute to more robust and defendable empirical agent-based modelling.
Author | : Dhinaharan Nagamalai |
Publisher | : Springer Science & Business Media |
Total Pages | : 753 |
Release | : 2011-09-14 |
Genre | : Computers |
ISBN | : 3642240429 |
This book constitutes the refereed proceedings of the First International Conference on Computer Science, Engineering and Information Technology, CCSEIT 2011, held in Tirunelveli, India, in September 2011. The 73 revised full papers were carefully reviewed and selected from more than 400 initial submissions. The papers feature significant contributions to all major fields of the Computer Science and Information Technology in theoretical and practical aspects.
Author | : Dirk Helbing |
Publisher | : Springer |
Total Pages | : 343 |
Release | : 2012-05-05 |
Genre | : Science |
ISBN | : 3642240046 |
What are the principles that keep our society together? This question is even more difficult to answer than the long-standing question, what are the forces that keep our world together. However, the social challenges of humanity in the 21st century ranging from the financial crises to the impacts of globalization, require us to make fast progress in our understanding of how society works, and how our future can be managed in a resilient and sustainable way. This book can present only a few very first steps towards this ambitious goal. However, based on simple models of social interactions, one can already gain some surprising insights into the social, ``macro-level'' outcomes and dynamics that is implied by individual, ``micro-level'' interactions. Depending on the nature of these interactions, they may imply the spontaneous formation of social conventions or the birth of social cooperation, but also their sudden breakdown. This can end in deadly crowd disasters or tragedies of the commons (such as financial crises or environmental destruction). Furthermore, we demonstrate that classical modeling approaches (such as representative agent models) do not provide a sufficient understanding of the self-organization in social systems resulting from individual interactions. The consideration of randomness, spatial or network interdependencies, and nonlinear feedback effects turns out to be crucial to get fundamental insights into how social patterns and dynamics emerge. Given the explanation of sometimes counter-intuitive phenomena resulting from these features and their combination, our evolutionary modeling approach appears to be powerful and insightful. The chapters of this book range from a discussion of the modeling strategy for socio-economic systems over experimental issues up the right way of doing agent-based modeling. We furthermore discuss applications ranging from pedestrian and crowd dynamics over opinion formation, coordination, and cooperation up to conflict, and also address the response to information, issues of systemic risks in society and economics, and new approaches to manage complexity in socio-economic systems. Selected parts of this book had been previously published in peer reviewed journals.
Author | : Todd K. BenDor |
Publisher | : CRC Press |
Total Pages | : 328 |
Release | : 2018-09-04 |
Genre | : Conflict management |
ISBN | : 9781138476035 |
This book examines the recent development and use of computer modeling and simulation as an important tool for understanding environmental and resource-based conflicts and for finding pathways for conflict resolution and cooperation. It introduces a new, innovative technique for using agent-based modeling (ABM) as a tool for better understanding environmental conflicts and discusses the application of agent-based modeling for the analysis of multi-agent interaction and conflict and demonstrates the natural interdisciplinary convergence. The authors explore numerous examples of environmental and resource conflicts around the world, as well as cooperative approaches for conflict resolution.
Author | : Joshua M. Epstein |
Publisher | : Princeton University Press |
Total Pages | : 379 |
Release | : 2012-01-02 |
Genre | : Business & Economics |
ISBN | : 1400842875 |
Agent-based computational modeling is changing the face of social science. In Generative Social Science, Joshua Epstein argues that this powerful, novel technique permits the social sciences to meet a fundamentally new standard of explanation, in which one "grows" the phenomenon of interest in an artificial society of interacting agents: heterogeneous, boundedly rational actors, represented as mathematical or software objects. After elaborating this notion of generative explanation in a pair of overarching foundational chapters, Epstein illustrates it with examples chosen from such far-flung fields as archaeology, civil conflict, the evolution of norms, epidemiology, retirement economics, spatial games, and organizational adaptation. In elegant chapter preludes, he explains how these widely diverse modeling studies support his sweeping case for generative explanation. This book represents a powerful consolidation of Epstein's interdisciplinary research activities in the decade since the publication of his and Robert Axtell's landmark volume, Growing Artificial Societies. Beautifully illustrated, Generative Social Science includes a CD that contains animated movies of core model runs, and programs allowing users to easily change assumptions and explore models, making it an invaluable text for courses in modeling at all levels.
Author | : Peter Hedström |
Publisher | : OUP Oxford |
Total Pages | : 795 |
Release | : 2011-01-06 |
Genre | : Social Science |
ISBN | : 0191615234 |
Analytical sociology is a strategy for understanding the social world. It is concerned with explaining important social facts such as network structures, patterns of residential segregation, typical beliefs, cultural tastes, and common ways of acting. It explains such facts by detailing in clear and precise ways the mechanisms through which the social facts were brought about. Making sense of the relationship between micro and macro thus is one of the central concerns of analytical sociology. The approach is a contemporary incarnation of Robert K. Merton's notion of middle-range theory and presents a vision of sociological theory as a tool-box of semi-general theories each of which is adequate for explaining certain types of phenomena. The Handbook brings together some of the most prominent sociologists in the world. Some of the chapters focus on action and interaction as the cogs and wheels of social processes, while others consider the dynamic social processes that these actions and interactions bring about.
Author | : Gary S. Metcalf |
Publisher | : Springer |
Total Pages | : 1443 |
Release | : 2021-07-28 |
Genre | : Business & Economics |
ISBN | : 9789811507199 |
The primary purpose of this handbook is to clearly describe the current state of theories of systems sciences and to support their use and practice. There are many ways in which systems sciences can be described. This handbook takes a multifaceted view of systems sciences and describes them in terms of a relatively large number of dimensions, from natural and engineering science to social science and systems management perspectives. It is not the authors’ intent, however, to produce a catalog of systems science concepts, methodologies, tools, or products. Instead, the focus is on the structural network of a variety of topics. Special emphasis is given to a cyclic–interrelated view; for example, when a theory of systems sciences is described, there is also discussion of how and why the theory is relevant to modeling or practice in reality. Such an interrelationship between theory and practice is also illustrated when an applied research field in systems sciences is explained. The chapters in the handbook present definitive discussions of systems sciences from a wide array of perspectives. The needs of practitioners in industry and government as well as students aspiring to careers in systems sciences provide the motivation for the majority of the chapters. The handbook begins with a comprehensive introduction to the coverage that follows. It provides not only an introduction to systems sciences but also a brief overview and integration of the succeeding chapters in terms of a knowledge map. The introduction is intended to be used as a field guide that indicates why, when, and how to use the materials or topics contained in the handbook.
Author | : Institute of Medicine |
Publisher | : National Academies Press |
Total Pages | : 269 |
Release | : 2015-07-17 |
Genre | : Medical |
ISBN | : 0309317258 |
Tobacco consumption continues to be the leading cause of preventable disease and death in the United States. The Food and Drug Administration (FDA) regulates the manufacture, distribution, and marketing of tobacco products - specifically cigarettes, cigarette tobacco, roll-your-own tobacco, and smokeless tobacco - to protect public health and reduce tobacco use in the United States. Given the strong social component inherent to tobacco use onset, cessation, and relapse, and given the heterogeneity of those social interactions, agent-based models have the potential to be an essential tool in assessing the effects of policies to control tobacco. Assessing the Use of Agent-Based Models for Tobacco Regulation describes the complex tobacco environment; discusses the usefulness of agent-based models to inform tobacco policy and regulation; presents an evaluation framework for policy-relevant agent-based models; examines the role and type of data needed to develop agent-based models for tobacco regulation; provides an assessment of the agent-based model developed for FDA; and offers strategies for using agent-based models to inform decision making in the future.