Growing Artificial Societies
is a groundbreaking book that posits a new mechanism for studying populations and their evolution. By combining the disciplines of cellular automata and "artificial life", Joshua M. Epstein and Robert Axtell have developed a mechanism for simulating all sorts of emergent behavior within a grid of cells managed by a computer. In their simulations, simple rules governing individuals' "genetics"" and their competition for foodstuffs result in highly complex societal behaviors. Epstein and Axtell explore the role of seasonal migrations, pollution, sexual reproduction, combat, and transmission of disease or even "culture" within their artificial world, using these results to draw fascinating parallels with real- world societies. In their simulation, for instance, allowing the members to "trade" increases overall well-being but also increases economic inequality. In Growing Artificial Societies
, the authors provide a workable framework for studying social processes in microcosm, a thoroughly fascinating accomplishment.
"Computer simulations are changing the frontiers of science. Growing Artificial Societies is an outstanding example of why; it shows how sociocultural phenomena like trade, wealth, and warfare arise naturally out of the simple actions of individuals. This illuminating, entertaining book will set the standard for the practice of social science in the 21st century."
(John L. Casti, Santa Fe Institute)
"Epstein and Axtell present an exciting theoretical version of an integrated social science built on simple and explicit microfoundations."
(Sidney G. Winter, Wharton School of Business)
Growing Artificial Societies is a milestone in social science research. It vividly demonstrates the potential of agent-based computer simulation to break disciplinary boundaries. It does this by analyzing, in a unified framework, the dynamic interactions of such diverse activities as trade, combat, mating, culture, and disease. It is an impressive achievement.
(Robert Axelrod, University of Michigan)