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Growing Artificial Societies: Social Science From the Bottom Up (Complex Adaptive Systems) 1St Edition Edition

3.8 out of 5 stars 11 customer reviews
ISBN-13: 978-0262550253
ISBN-10: 0262550253
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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

"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)
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Product Details

  • Series: Complex Adaptive Systems
  • Paperback: 228 pages
  • Publisher: Brookings Institution Press & MIT Press; 1St Edition edition (October 1, 1996)
  • Language: English
  • ISBN-10: 0262550253
  • ISBN-13: 978-0262550253
  • Product Dimensions: 6 x 0.5 x 8.9 inches
  • Shipping Weight: 15.5 ounces (View shipping rates and policies)
  • Average Customer Review: 3.8 out of 5 stars  See all reviews (11 customer reviews)
  • Amazon Best Sellers Rank: #295,697 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

Format: Paperback
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.
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Format: 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.
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Format: Paperback
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.
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Format: Paperback
The idea of the "generative" approach to social science, as described in this book, is that we attempt to understand the workings of a society not through "discursive" models (as in qualitative social science) or through game theoretical models with extremely simplified assumptions and homogeneous agents (as in more "quantitative" approaches), but by creating a simplified version of the society and letting it "run." So we use software (or pen and paper; Schelling's pioneering models of segregation were studied without the benefit of a computer) to generate an environment and simplified agents that interact with one another, and then we see what happens. The advantages of this approach is that one can add complexity to a model in a controlled manner and study the resulting dynamics (rather than merely static equilibria); so, for example, one might start with agents who move and eat, then see what happens if you add the ability to trade, and so on (besides, it's fun to play around with such models). The disadvantages, however, come from the very flexibility of the approach, which allows for highly complex models: it is sometimes hard to tell whether or not a particularly interesting result is simply an artifact of the simulation or the consequence of some particular simplifying assumption (though it should be noted that the same is often true of traditional models, where striking results, like the pareto-optimality of free markets, are sometimes basically artifacts of the simplifying assumptions made for the sake of creating "tractable" models).

Epstein and Axtell report in this book the results of a pioneering 1994 simulation: "Sugarland".
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Format: Paperback Verified Purchase
This is one of the most important books on social sciences ever published! The sugarscape is one of the first agent based models in economics. It models agents on an islan of sugar and shows sole emerging patterns: the inequality of wealth due to differences in the metabolism, differences in sight and the place where the agents start their life! Without markets, inequality seems to be unavoidable if nature is left to go its way.
After this second chapter, of which the importance cannot be denied, the authors spend another chapter on the impact of reproduction, acculturation and combat. All these seem to enhance inequality in the first place, but later on replacement of the population by the most succsesful.
The most difficult part is the chapter on trade, where sugar is being exchanged for spice. Unfortunately, the authors do not succeed in developing a strong model. I am sure, a good trade model in ABM will be able to replace the flawed law of supply and demand of the neoclassical economics. This law calculates an equilibrium which is believed to be u,qiue and efficient. Nothing is less true: an equilibrium can be attained, but only in special circumstances and after a long intermediate period in which feedback processes play an important role. Prices are determined locally: there is no single price, only a statistical average! The authors show different distributions of prices and volumes of trade. This chapter should be considered a clear falsification of neoclassical theory.
Strangely, the next chapter deals with disease! They want to show agent based models can be used in seceral social sciences: economics, demographics, sociology and even medicine.
In the concluding chapter, they repeat this objective.
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