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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.
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 book focuses on the new possibilities and approaches to social modeling currently being made possible by an unprecedented variety of datasets generated by our interactions with modern technologies. This area has witnessed a veritable explosion of activity over the last few years, yielding many interesting and useful results. Our aim is to provide an overview of the state of the art in this area of research, merging an extremely heterogeneous array of datasets and models. Social Phenomena: From Data Analysis to Models is divided into two parts. Part I deals with modeling social behavior under normal conditions: How we live, travel, collaborate and interact with each other in our daily lives. Part II deals with societal behavior under exceptional conditions: Protests, armed insurgencies, terrorist attacks, and reactions to infectious diseases. This book offers an overview of one of the most fertile emerging fields bringing together practitioners from scientific communities as diverse as social sciences, physics and computer science. We hope to not only provide an unifying framework to understand and characterize social phenomena, but also to help foster the dialogue between researchers working on similar problems from different fields and perspectives.
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).
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.
A description of computer programs for simulating phenomena in hydrodynamics, gas dynamics, and elastic plastic flow in one, two, and three dimensions. The text covers Maxwell's equations, and thermal and radiation diffusion, while the numerical procedures described permit the exact conservation of physical properties in the solutions of the fundamental laws of mechanics. The author also treats materials, including the use of simulation programs to predict material behavior.
In this captivating yet troubling book, Ian Shapiro offers a searing indictment of many influential practices in the social sciences and humanities today. Perhaps best known for his critique of rational choice theory, Shapiro expands his purview here. In discipline after discipline, he argues, scholars have fallen prey to inward-looking myopia that results from--and perpetuates--a flight from reality. In the method-driven academic culture we inhabit, argues Shapiro, researchers too often make display and refinement of their techniques the principal scholarly activity. The result is that they lose sight of the objects of their study. Pet theories and methodological blinders lead unwelcome facts to be ignored, sometimes not even perceived. The targets of Shapiro's critique include the law and economics movement, overzealous formal and statistical modeling, various reductive theories of human behavior, misguided conceptual analysis in political theory, and the Cambridge school of intellectual history. As an alternative to all of these, Shapiro makes a compelling case for problem-driven social research, rooted in a realist philosophy of science and an antireductionist view of social explanation. In the lucid--if biting--prose for which Shapiro is renowned, he explains why this requires greater critical attention to how problems are specified than is usually undertaken. He illustrates what is at stake for the study of power, democracy, law, and ideology, as well as in normative debates over rights, justice, freedom, virtue, and community. Shapiro answers many critics of his views along the way, securing his position as one of the distinctive social and political theorists of our time.
This book presents a method for creating a working model of society, using data systems and simulation techniques, that can be used for testing propositions of scientific and policy nature. The model is based on the example of New Zealand, but will be applicable to other countries. It is expected that collaborators in other countries can emulate this example with their data systems for teaching and policy purposes, producing a cross-national "collaboratory". This enterprise will evolve with, and to a degree independently of, the book itself, with a supporting website as well as teaching and scientific initiatives. Readers of this text will, for the first time, have a simulation-based working model of society that can be interrogated for policy and substantive purposes. This book will appeal to researchers and professionals from various disciplines working within the social sciences, particularly on matters of demography and public policy.
Social sciences -- Simulation methods. Social interaction -- Computer simulation. Social sciences -- Mathematical models. (publisher)
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.