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Complex Adaptive Systems: An Introduction to Computational Models of Social Life by John H. Miller, Scott E. Page
  

Complex Adaptive Systems: An Introduction to Computational Models of Social Life

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Part of the Princeton Studies in Complexity Series

Synopsis

Complex Adaptive Systems: An Introduction to Computational Models of Social Life by John H. Miller, Scott E. Page

This book provides the first clear, comprehensive, and accessible account of complex adaptive social systems, by two of the field's leading authorities. Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.

About the Author

John H. Miller is professor of economics and social sciences at Carnegie Mellon University. Scott E. Page is professor of complex systems, political science, and economics at the University of Michigan. He is the author of The Difference (Princeton).

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Book Info

Publication date

5th March 2007

Author

John H. Miller, Scott E. Page

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Publisher

Princeton University Press

Format

Paperback
288 pages

Categories

Social research & statistics
Chaos theory

ISBN

9780691127026

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