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Agent-based modeling and social simulation have emerged as an interdisciplinary area of social science that includes computational economics, organizational science, social dynamics, and complex systems. This area contributes to enriching our understanding of the fundamental processes of social phenomena caused by complex interactions among agents. Bringing together diverse approaches to social simulation and research agendas, this book presents a unique collection of contributions from the Second World Congress on Social Simulation, held in 2008 at George Mason University in Washington DC, USA. This book in particular includes articles on norms, diffusion, social networks, economy, markets and organizations, computational modeling, and programming environments, providing new hypotheses and theories, new simulation experiments compared with various data sets, and new methods for model design and development. These works emerged from a global and interdisciplinary scientific community of the three regional scientific associations for social simulation: the North American Association for Computational Social and Organizational Science (NAACSOS; now the Computational Social Science Society, CSSS), the European Social Simulation Association (ESSA), and the Pacific Asian Association for Agent-bBased Approach in Social Systems Sciences (PAAA).
In this book experts from quite different fields present simulations of social phenomena: economists, sociologists, political scientists, psychologists, cognitive scientists, organisational scientists, decision scientists, geographers, computer scientists, AI and AL scientists, mathematicians and statisticians. They simulate markets, organisations, economic dynamics, coalition formation, the emergence of cooperation and exchange, bargaining, decision making, learning, and adaptation. The history, problems, and perspectives of simulating social phenomena are explicitly discussed.
This book studies social phenomena in a new way, by making judicious use of computer technology. The book addresses the entire spectrum of classic studies in social science, from experiments to the computational models, with a multidisciplinary approach. The book is suitable for those who want to get a picture of what it means to do social research today, and also to get an indication of the major open issues. The book is connected to a database of code for simulations, experimental data and allows to activate a subscription to a teaching tool using NetLogo, a programming language widely used in the social studies. The authors are researchers with first-hand experience research projects, both basic and applied. The work will be useful for those who want to understand more of the social, economic and political phenomena via computer applications.
Social simulation can be a difficult discipline to encompass fully. There are many methods, models, directions, and theories that can be discussed and applied to various social sciences. Anthropology, sociology, political science, economy, government, and management can all benefit from social simulation. Interdisciplinary Applications of Agent-Based Social Simulation and Modeling aims to bring a different perspective to this interdisciplinary topic. This book presents current discussions and new insights on social simulation as a whole, focusing on its dangers, pitfalls, deceits, and challenges. This book is an essential reference for researchers in this field, professionals using social simulation, and even students studying this discipline.
This book explores the intersection between individual cognitive modeling and modeling of multi-agent interaction.
The most exciting and productive areas of academic inquiry are often where the interests of two disciplines meet. This is certainly the case for the subject of this book, originally published in 1994, which explores the contribution that computer-based modelling and artificial intelligence can make to understanding fundamental issues in social science. Simulating Societies shows how computer simulations can help to clarify theoretical approaches, contribute to the evaluation of alternative theories, and illuminate one of the major issues of the social sciences: how social phenomena can "emerge" from individual action. The authors discuss how simulation models can be constructed using recently developed artificial intelligence techniques and they consider the methodological issues involved in using such models for theory development, testing and experiment. The introductory chapters situate the book within social science, and suggest why the time was ripe for significant progress, before defining basic terminology, showing how simulation has been used to theorize about organizations, and indicating through examples some of the fundamental issues involved in simulation. The main body of the text provides case studies drawn from economics, anthropology, archaeology, planning, social psychology and sociology. The appeal of this path-breaking book was twofold. It offered an essential introduction to simulation for social scientists and it provided case study applications for computer scientists interested in the latest advances in the burgeoning area of distributed artificial intelligence (DAI) at the time.
This textbook provides a comprehensive and reader-friendly introduction to the field of computational social science (CSS). Presenting a unified treatment, the text examines in detail the four key methodological approaches of automated social information extraction, social network analysis, social complexity theory, and social simulation modeling. This updated new edition has been enhanced with numerous review questions and exercises to test what has been learned, deepen understanding through problem-solving, and to practice writing code to implement ideas. Topics and features: contains more than a thousand questions and exercises, together with a list of acronyms and a glossary; examines the similarities and differences between computers and social systems; presents a focus on automated information extraction; discusses the measurement, scientific laws, and generative theories of social complexity in CSS; reviews the methodology of social simulations, covering both variable- and object-oriented models.
This volume groups together the papers accepted for the 6th InternationalWorkshop on Multi-Agent-Based Simulation (MABS 2005), co-located with the 4th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2005), which occurred in Utrecht, The Netherlands, on July 25, 2005.
This book presents the state of the art in social simulation as presented at the Social Simulation Conference 2019 in Mainz, Germany. It covers the developments in applications and methods of social simulation, addressing societal issues such as socio-ecological systems and policymaking. Methodological issues discussed include large-scale empirical calibration, model sharing and interdisciplinary research, as well as decision-making models, validation and the use of qualitative data in simulation modeling. Research areas covered include archaeology, cognitive science, economics, organization science and social simulation education. This book gives readers insight into the increasing use of social simulation in both its theoretical development and in practical applications such as policymaking whereby modeling and the behavior of complex systems is key. The book appeals to students, researchers and professionals in the various fields.
Social sciences -- Simulation methods. Social interaction -- Computer simulation. Social sciences -- Mathematical models. (publisher)