Generative Social Science: Studies in Agent-Based Computational Modeling

Joshua M. Epstein

2012年1月 · Princeton Studies in Complexity 第 21 冊 · Princeton University Press

關於這本電子書

Agent-based computational modeling is changing the face of social science. In Generative Social Science, Joshua Epstein argues that this powerful, novel technique permits the social sciences to meet a fundamentally new standard of explanation, in which one "grows" the phenomenon of interest in an artificial society of interacting agents: heterogeneous, boundedly rational actors, represented as mathematical or software objects. After elaborating this notion of generative explanation in a pair of overarching foundational chapters, Epstein illustrates it with examples chosen from such far-flung fields as archaeology, civil conflict, the evolution of norms, epidemiology, retirement economics, spatial games, and organizational adaptation. In elegant chapter preludes, he explains how these widely diverse modeling studies support his sweeping case for generative explanation.

This book represents a powerful consolidation of Epstein's interdisciplinary research activities in the decade since the publication of his and Robert Axtell's landmark volume, Growing Artificial Societies. Beautifully illustrated, Generative Social Science includes a CD that contains animated movies of core model runs, and programs allowing users to easily change assumptions and explore models, making it an invaluable text for courses in modeling at all levels.

關於作者

Joshua M. Epstein is a Senior Fellow in Economic Studies at the Brookings Institution, a founding member of the Brookings-Johns Hopkins Center on Social and Economic Dynamics, and a member of the External Faculty of the Santa Fe Institute. He is the coauthor of Growing Artificial Societies: Social Science from the Bottom Up and the author of Nonlinear Dynamics, Mathematical Biology, and Social Science.