Rainer Hegselmann

Modelling and Simulation in the Social Sciences from the Philosophy of Science Point of View - Theory and Decision Library A: Rainer Hegselmann 1996 edition

Marc Notes: Includes bibliographical references and indexes. Review Quotes: Overall, this is an excellent collection of articles that cover a wide spectrum from the social and natural sciences. It would make a nice companion piece to Chaos Theory in the Social Sciences by Kiel and Elliott. ... There is a rich diversity in approach, subject matter and expertise. ... Hegselmann, Mueller and Troitzsch have put together an extraordinary book that I highly recommend.' Journal of Artificial Societies and Social Simulation (2001) Table of Contents: Preface. 1. Holism, Individualism and Emergent Properties. An Approach from the Perspective of Simulation; G. N. Gilbert. 2. Simulation and Rational Practice; H. Kliemt. 3. Epistemic Cultures in the Social Sciences. The Modelling Dilemma Dissolved; K. H. Muller. 4. Impossible Models; U. Krause. 5. The World as a Process. Simulations in the Natural and Social Sciences; S. Hartmann. 6. Evolutionary Explanations from a Philosophy of Science Point of View; U. Mueller. 7. Some Thoughts on the Methodological Status of the Darmstadt Micro Macro Simulator (DMMS); H.-D. Heike. 8. On the Measurement of Action; W. Balzer. 9. Structuralist Models, Idealization, and Approximation; C. U. Moulines. 10. A Concept of Explanation for Social Interaction Models; H. Westmeyer. 11. Simulation and Structuralism; K. G. Troitzsch. 12. Cellular Automata in the Social Sciences. Perspectives, Restrictions, and Artefacts; R. Hegselmann. 13. Computer Simulations of Sustainable Cooperation in Social Dilemmas; W. B. G. Liebrand, W. M. Messick. 14. Modeling Social Change with Cellular Automata; A. Nowak, M. Lewenstein. 15. Dynamic Social Impact. Robust Predictions from Simple Theory; B. Latane. Index."Publisher Marketing: 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.

Contributor Bio:  Mueller, Ulrich Mueller is Professor at the Institut fur Germanistik at the Universitat Salzburg.