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Simulating Social Complexity

Author: Bruce Edmonds

Publisher: Springer

Published: 2017-11-24

Total Pages: 838

ISBN-13: 3319669486

This volume examines all aspects of using agent or individual-based simulation. This approach represents systems as individual elements having their own set of differing states and internal processes. The interactions between elements in the simulation represent interactions in the target systems. What makes this "social" is that it can represent an observed society. Social systems include all those systems where the components have individual agency but also interact with each other. This includes human societies and groups, but also increasingly socio-technical systems where the internet-based devices form the substrate for interaction. These systems are central to our lives, but are among the most complex known. This poses particular problems for those who wish to understand them. The complexity often makes analytic approaches infeasible but, on the other hand, natural language approaches are also inadequate for relating intricate cause and effect. This is why individual and agent-based computational approaches hold out the possibility of new and deeper understanding of such systems. This handbook marks the maturation of this new field. It brings together summaries of the best thinking and practices in this area from leading researchers in the field and constitutes a reference point for standards against which future methodological advances can be judged. This second edition adds new chapters on different modelling purposes and applying software engineering methods to simulation development. Revised existing content will keep the book up-to-date with recent developments. This volume will help those new to the field avoid "reinventing the wheel" each time, and give them a solid and wide grounding in the essential issues. It will also help those already in the field by providing accessible overviews of current thought. The material is divided into four sections: Introduction, Methodology, Mechanisms, and Applications. Each chapter starts with a very brief section called ‘Why read this chapter?’ followed by an abstract, which summarizes the content of the chapter. Each chapter also ends with a section on ‘Further Reading’. Whilst sometimes covering technical aspects, this second edition of Simulating Social Complexity is designed to be accessible to a wide range of researchers, including both those from the social sciences as well as those with a more formal background. It will be of use as a standard reference text in the field and also be suitable for graduate level courses.

Simulating Social Complexity

Author:

Publisher:

Published: 2013

Total Pages:

ISBN-13: 9783540939481

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Social systems are among the most complex known. This poses particular problems for those who wish to understand them. The complexity often makes analytic approaches infeasible and natural language approaches inadequate for relating intricate cause and effect. However, individual- and agent-based computational approaches hold out the possibility of new and deeper understanding of such systems. Simulating Social Complexity examines all aspects of using agent- or individual-based simulation. This approach represents systems as individual elements having each their own set of differing states and internal processes. The interactions between elements in the simulation represent interactions in the target systems. What makes these elements "social" is that they are usefully interpretable as interacting elements of an observed society. In this, the focus is on human society, but can be extended to include social animals or artificial agents where such work enhances our understanding of human society. The phenomena of interest then result (emerge) from the dynamics of the interaction of social actors in an essential way and are usually not easily simplifiable by, for example, considering only representative actors. The introduction of accessible agent-based modelling allows the representation of social complexity in a more natural and direct manner than previous techniques. In particular, it is no longer necessary to distort a model with the introduction of overly strong assumptions simply in order to obtain analytic tractability. This makes agent-based modelling relatively accessible to a range of scientists. The outcomes of such models can be displayed and animated in ways that also make them more interpretable by experts and stakeholders. This handbook is intended to help in the process of maturation of this new field. It brings together, through the collaborative effort of many leading researchers, summaries of the best thinking and practice in this area and constitutes a reference point for standards against which future methodological advances are judged. This book will help those entering into the field to avoid "reinventing the wheel" each time, but it will also help those already in the field by providing accessible overviews of current thought. The material is divided into four sections: Introductory, Methodology, Mechanisms, and Applications. Each chapter starts with a very brief section called 'Why read this chapter?' followed by an abstract, which summarizes the content of the chapter. Each chapter also ends with a section of 'Further Reading' briefly describing three to eight items that a newcomer might read next.

Social Self-Organization

Author: Dirk Helbing

Publisher: Springer

Published: 2012-05-05

Total Pages: 343

ISBN-13: 3642240046

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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.

Simulation of Financial Markets with Agent-Based Model

Author: Hajime Kita

Publisher: Springer

Published: 2015-12-25

Total Pages: 0

ISBN-13: 9784431550563

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This book takes up unique agent-based approaches to solving problems related to stock and their derivative markets. Toward this end, the authors have worked for more than 15 years on the development of an artificial market simulator called U-Mart for use as a research and educational tool. A noteworthy feature of the U-Mart simulator compared to other artificial market simulators is that U-Mart is an ultra-realistic artificial stock and their derivative market simulator. For example, it can simulate “arrowhead,” a next-generation trading system used in the Tokyo Stock Exchange and other major markets, as it takes into consideration the institutional design of the entire market. Another interesting feature of the U-Mart simulator is that it permits both human and computer programs to participate simultaneously as traders in the artificial market. In this book, first the details of U-Mart are explained, enabling readers to install and run the simulator on their computers for research and educational purposes. The simulator thus can be used for gaming simulation of the artificial market and even for users as agents to implement their own trading strategies for agent-based simulation (ABS).The book also presents selected research cases using the U-Mart simulator. Here, topics include automated acquisition of trading strategy using artificial intelligence techniques, evaluation of a market maker system to treat thin markets such as those for small and regional businesses, systemic risk analysis of the financial market considering institutional design of the market, and analysis of how humans behave and learn in gaming simulation. New perspectives on artificial market research are provided, and the power, potential, and challenge of ABS are discussed. As explained in this important work, ABS is considered to be an effective tool as the third approach of social science, an alternative to traditional literary and mathematical approaches.

Modeling Complexity in Economic and Social Systems

Author: Frank Schweitzer

Publisher: World Scientific

Published: 2002-12-09

Total Pages: 404

ISBN-13: 9814488356

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Economics and the social sciences are, in fact, the “hard” sciences, as Herbert Simon argued, because the complexity of the problems dealt with cannot simply be reduced to analytically solvable models or decomposed into separate subprocesses. Nevertheless, in recent years, the emerging interdisciplinary “sciences of complexity” have provided new methods and tools for tackling these problems, ranging from complex data analysis to sophisticated computer simulations. In particular, advanced methods developed in the natural sciences have recently also been applied to social and economic problems. The twenty-one chapters of this book reflect this modern development from various modeling perspectives (such as agent-based models, evolutionary game theory, reinforcement learning and neural network techniques, time series analysis, non-equilibrium macroscopic dynamics) and for a broad range of socio-economic applications (market dynamics, technological evolution, spatial dynamics and economic growth, decision processes, and agent societies). They jointly demonstrate a shift of perspective in economics and the social sciences that is allowing a new outlook in this field to emerge. Contents:Market Dynamics:Trading Behavior and Excess Volatility in Toy Markets (M Marsili & D Challet)Percolation Models of Financial Market Dynamics (D Stauffer)Electrodynamical Model of Quasi-Efficient Financial Markets (K N Ilinski & A S Stepanenko)Multi-Agent Market Modeling of Foreign Exchange Rates (G Zimmermann et al.)Forecasting Price Increments Using an Artificial Neural Network (F Castiglione)Spectral Regularization, Data Complexity and Agent Behavior (A Ilyinsky)Technological Evolution:Dynamics of Economic and Technological Search Processes in Complex Adaptive Landscapes (W Ebeling et al.)New Results in a Self-Organized Model of Technological Evolution (A Arenas et al.)Firms' Decision-Making Process in an Evolutionary Model of Industrial Dynamics (W Kwasnicki)Spatial Dynamics and Economic Growth:Modelling Migration and Economic Agglomeration with Active Brownian Particles (F Schweitzer)The Evolution of Industrial Clusters — Simulating Spatial Dynamics (T Brenner & N Weigelt)The Growth Dynamics of German Business Firms (J Voit)A Dynamic Theory of a Firm: An Application of ‘Economic Forces’ (M Estola)Decision Processes:Adaptive Platform Dynamics in Multi-Party Spatial Voting (B M R Stadler)Subtle Nonlinearity in Popular Album Charts (R A Bentley & H D G Maschner)Dynamical Aspects in the Adoption of Agri-Environmental Measures (G Weisbuch & G Boudjema)Collective Choice and Mutual Knowledge Structures (D Richards et al.)Agent Societies:Evolutionary Study of Interethnic Co-Operation (V Kvasnicka & J Pospichal)Coalition Factor in the Evolution of Non-Kin Altruism (J-L Dessalles)Optimal Payoff Functions for Members of Collectives (D H Wolpert & K Tumer)A Day at the Beach: Human Agents Self-Organizing on the Sand Pile (H Ishii et al.) Readership: Researchers in the field of complex system science, economists, sociologists, physicists with an interdisciplinary focus, graduates, and professionals. Keywords:

Systems and Models

Author: Hartmut Bossel

Publisher: BoD – Books on Demand

Published: 2007

Total Pages: 374

ISBN-13: 3833481218

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A multitude of complex systems and actors pursuing their own agenda shape the dynamics of our world. Better understanding of their actions and interactions is crucial, and can be achieved by a profound knowledge of systems and their properties, and their representation in models allowing simulation of probable behavior. Drawing on his extensive research and teaching experience in modeling and simulation of a wide range of systems - from engineering to social systems and ecosystems - the author presents the fundamental concepts and approaches for understanding and modeling the complex systems shaping the dynamics of our world. The book applies state space analysis and system dynamics to deal with the dynamic processes of "causal systems," discusses information processing approaches for modeling decision processes of "actors" and "agents," and uses aspects of the coevolutionary development of systems in their environment to deal with normative orientation, ethics, and evaluation of policies and long-term development. The concepts are applied in particular to the issue of sustainable development of human society in an evolving world. The book is complemented by a survey of system topics and of models from many fields, and by an extensive bibliography on the many systems-related subjects covered. Hartmut Bossel is Professor Emeritus of environmental systems analysis. He taught for many years at the University of California in Santa Barbara and the University of Kassel, Germany, where he was director of the Center for Environmental Systems Research until his retirement. He holds an engineering degree from the Technical University of Darmstadt, and a Ph.D. degree from the University of California at Berkeley. With a background in engineering, systems science, and mathematical modeling, he has led many research projects and future studies in different countries, developing computer simulation models and decision support systems in the areas of energy supply policy, global dynamics, orientation of behavior, agricultural policy, and forest dynamics and management. He has written numerous books on modeling and simulation of dynamic systems, social change and future paths, and has published widely in the scientific literature in several fields. Bossel is author of a System Zoo containing over one hundred simulation models of diverse systems.