Growing Artificial Societies: Social Science from the Bottom Up (Complex Adaptive Systems) (Paperback)

~ (Author), Robert L. Axtell (Author)

Editorial Reviews

Amazon.com Review

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.

Review

"The ambitious aim of the authors is to propose a `generative programme for the social sciences and they see the artificial society as its principal scientific instrument.' This may or not become the case, but what they have achieved is to develop a method that reflects and is appropriate to the evolutionary process it studies ." -- Eve Mittleton-Kelly, The Times Higher Education Supplement, April 30, 1999

"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

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Product Details

• Paperback: 224 pages
• Publisher: The MIT Press; 1st Printing edition (November 8, 1996)
• Language: English
• ISBN-10: 0262550253
• ISBN-13: 978-0262550253
• Product Dimensions: 9 x 6.1 x 0.5 inches
• Shipping Weight: 14.4 ounces (View shipping rates and policies)
• Average Customer Review: 3.4 out of 5 stars  See all reviews (7 customer reviews)
• Amazon.com Sales Rank: #620,620 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

21 of 24 people found the following review helpful:

2.0 out of 5 stars Good simulation, poor basis, riddled with errors, May 6, 1998

By A Customer

This review is from: Growing Artificial Societies: CD-ROM + book (Complex Adaptive Systems) (Paperback)

This book was part of a graduate research class I was in. We built thier simulation from the ground up, but found many errors and simulation artifacts with in the book. Though the simulation was a very good one, they left or ignored key details, and the book only discusses the conceptual model. Building the model from the information in the book can be an exercise in futility. They do not give much detail, and what they do give, they hide within footnotes and seperate critical information with pages of analysis. The alanysis unfortunately doesn't talk about model deficiencies and other simulation artifacts the modelers introduced. In the end, an excellent simulation, regardless of how they put it together, and the errors their model injected into it.

9 of 9 people found the following review helpful:

4.0 out of 5 stars This is not a "how-to" book, August 8, 2005

By	MDK (British Columbia) - See all my reviews

This book is not a "how-to" book. They do not provide all of the code for thier sugarscape model. Yes, they provide some snap-shots of code for the reader, but those are instructive as to how to organize one's own code for your own ideas and models. If you want the entire code go to Swarm or RePast web pages and look for it in objective C or Java.

I was introduced to this book in a graduate archaeology course. Now, 3 years later I've returned to it for my dissertation. What this book does it explain how simple rules and ideas can create rather complex outcomes. What are the affects of having agents vision be only 5 cells compared to infinite sight? Can simple biological questions such as resolution of vision have a profound affect on our social structure? There are a bunch of, respectively, simple questions that this book address or introduce to explain the power of this method for the social sciences.

If one is looking for a "How To Book" you should go to Ascape, RePast, Swarm, or any of the other agent based modeling software research groups. What this book does is provide the reader with the conceptual issues and the foundation for what this method can do, that's it.

7 of 8 people found the following review helpful:

5.0 out of 5 stars The Future of Modeling Social Systems, October 15, 2004

By	Gregory Schmidt (Aurora Ohio) - See all my reviews (REAL NAME)

The authors do an impressive job of demonstrating how agent based simulations can be applied to social systems. In the past, modeling of this sort was limited to traditional analysis techniques such as applied differential equations. While some are critical of this work because they point out the number of assumptions inherent in this model, they also neglect to consider the greater degree of assumptions and over-simplifications implicit in pure mathematical models (eg, linearity, continuous functions, etc.) An advantage of agent based modeling is that one can consider all sorts of rules which do not lend themselves to purely mathematical models. Consider queuing theory as an example. While there exist basic mathematical models for queue analysis, once a certain threshold of complexity is reached, these models fail, and one must look to computer simulation as the alternative. While their results are speculative, the authors have successfully demonstrated emergence of complex behavior from simple rules. One such example is an unexpected diagonal migration path emerging from an orthogonal movement rule.
In the future, this type of social modeling will be the accepted norm and practitioners will look back at this work as a foundational reference.