Simulation For The Social Scientist


Book Description

Social sciences -- Simulation methods. Social interaction -- Computer simulation. Social sciences -- Mathematical models. (publisher)




Simulation for the Social Scientist


Book Description

What can computer simulation contribute to the social sciences? Which of the many approaches to simulation would be best for my social science project? How do I design, carry out and analyse the results from a computer simulation? Interest in social simulation has been growing rapidly worldwide as a result of increasingly powerful hardware and software and also a rising interest in the application of ideas of complexity, evolution, adaptation and chaos in the social sciences. Simulation for the Social Scientist is a practical textbook on the techniques of building computer simulations to assist understanding of social and economic issues and problems. This authoritative book details all the common approaches to social simulation, to provide social scientists with an appreciation of the literature and allow those with some programming skills to create their own simulations. New for this edition: A new chapter on designing multi-agent systems, to support the fact that multi-agent modelling has become the most common approach to simulation New examples and guides to current software Updated throughout to take new approaches into account The book is an essential tool for social scientists in a wide range of fields, particularly sociology, economics, anthropology, geography, organizational theory, political science, social policy, cognitive psychology and cognitive science. It will also appeal to computer scientists interested in distributed artificial intelligence, multi-agent systems and agent technologies.




Modelling and Simulation in the Social Sciences from the Philosophy of Science Point of View


Book Description

Model building in the social sciences can increasingly rely on well elaborated formal theories. At the same time inexpensive large computational capacities are now available. Both make computer-based model building and simulation possible in social science, whose central aim is in particular an understanding of social dynamics. Such social dynamics refer to public opinion formation, partner choice, strategy decisions in social dilemma situations and much more. In the context of such modelling approaches, novel problems in philosophy of science arise which must be analysed - the main aim of this book. Interest in social simulation has recently been growing rapidly world- wide, mainly as a result of the increasing availability of powerful personal computers. The field has also been greatly influenced by developments in cellular automata theory (from mathematics) and in distributed artificial intelligence which provided tools readily applicable to social simulation. This book presents a number of modelling and simulation approaches and their relations to problems in philosophy of science. It addresses sociologists and other social scientists interested in formal modelling, mathematical sociology, and computer simulation as well as computer scientists interested in social science applications, and philosophers of social science.




Monte Carlo Simulation and Resampling Methods for Social Science


Book Description

Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, this book examines abstract principles, such as bias, efficiency, and measures of uncertainty in an intuitive, visual way. Instead of thinking in the abstract about what would happen to a particular estimator "in repeated samples," the book uses simulation to actually create those repeated samples and summarize the results. The book includes basic examples appropriate for readers learning the material for the first time, as well as more advanced examples that a researcher might use to evaluate an estimator he or she was using in an actual research project. The book also covers a wide range of topics related to Monte Carlo simulation, such as resampling methods, simulations of substantive theory, simulation of quantities of interest (QI) from model results, and cross-validation. Complete R code from all examples is provided so readers can replicate every analysis presented using R.




Social Simulation


Book Description

"This book, a reference survey of social simulation work comprehensively collects the most exciting developments in the field. Drawing research contributions from a vibrant community of experts on social simulation, it provides a set of unique and innovative approaches, ranging from agent-based modeling to empirically based simulations, as well as applications in business, governmental, scientific, and other contexts"--Provided by publisher.




Introduction to Computational Social Science


Book Description

This reader-friendly textbook is the first work of its kind to provide a unified Introduction to Computational Social Science (CSS). Four distinct methodological approaches are examined in detail, namely automated social information extraction, social network analysis, social complexity theory and social simulation modeling. The coverage of these approaches is supported by a discussion of the historical context, as well as by a list of texts for further reading. Features: highlights the main theories of the CSS paradigm as causal explanatory frameworks that shed new light on the nature of human and social dynamics; explains how to distinguish and analyze the different levels of analysis of social complexity using computational approaches; discusses a number of methodological tools; presents the main classes of entities, objects and relations common to the computational analysis of social complexity; examines the interdisciplinary integration of knowledge in the context of social phenomena.




Simulating Social Phenomena


Book Description

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.




Science in the Age of Computer Simulation


Book Description

Computer simulation was first pioneered as a scientific tool in meteorology and nuclear physics in the period following World War II, but it has grown rapidly to become indispensible in a wide variety of scientific disciplines, including astrophysics, high-energy physics, climate science, engineering, ecology, and economics. Digital computer simulation helps study phenomena of great complexity, but how much do we know about the limits and possibilities of this new scientific practice? How do simulations compare to traditional experiments? And are they reliable? Eric Winsberg seeks to answer these questions in Science in the Age of Computer Simulation. Scrutinizing these issue with a philosophical lens, Winsberg explores the impact of simulation on such issues as the nature of scientific evidence; the role of values in science; the nature and role of fictions in science; and the relationship between simulation and experiment, theories and data, and theories at different levels of description. Science in the Age of Computer Simulation will transform many of the core issues in philosophy of science, as well as our basic understanding of the role of the digital computer in the sciences.




Simulating Societies


Book Description

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.




The Science and Art of Simulation I


Book Description

The new book series “The Science and Art of Simulation” (SAS) addresses computer simulations as a scientific activity and engineering artistry (in the sense of a technē). The first volume is devoted to three topics: 1. The Art of Exploring Computer Simulations Philosophy began devoting attention to computer simulations at a relatively early stage. Since then, the unquestioned point of view has been that computer simulation is a new scientific method; the philosophy of simulation is therefore part of the philosophy of science. The first section of this volume discusses this implicit, unchallenged assumption by addressing, from different perspectives, the question of how to explore (and how not to explore) research on computer simulations. Scientists discuss what is still lacking or considered problematic, while philosophers draft new directions for research, and both examine the art of exploring computer simulations. 2. The Art of Understanding Computer Simulations The results of computer simulations are integrated into both political and social decisions. It is implicitly assumed that the more detailed, and consequently more realistic, a computer simulation is, the more useful it will be in decision-making. However, this idea is by no means justified. Different types of computer simulations have to be differentiated, which in turn requires the specific skill of understanding computer simulation results. The articles in this section examine the capabilities and limits of simulation results in political and social contexts, exploring the art of understanding computer simulation results. 3. The Art of Knowing through Computer Simulations? The advent of computer simulation in today’s scientific practices challenges the order of science. What kind of knowledge is gained through computer simulations is the key question in this section. Computer simulations are often compared to experiments or to arguments, and the transformation of our traditional scientific notions might be more challenging than expected – these Ideas are put forward in the third section to conceptualize the art of knowing through computer simulations.