Complex Adaptive Systems: An Introduction to Computational Models of Social Life
Language: English
Published by Princeton University Press, 2007
- Softcover
- New

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2007. Paperback. Provides an account of complex adaptive social systems, by two of the field's leading authorities. This work 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 also demonstrates how the usual extremes used in modeling can be fruitfully transcended. Series: Princeton Studies in Complexity. Num Pages: 288 pages, 18 halftones. 16 line illus. 42 tables. BIC Classification: JHBC; PBWS. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 233 x 155 x 17. Weight in Grams: 434. . . . . . Books ship from the US and Ireland.
Seller Inventory # V9780691127026
- Title
- Complex Adaptive Systems: An Introduction to Computational Models of Social Life
- Author
- John H. Miller
- Publisher
- Princeton University Press
- Publication year
- 2007
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 0691127026
- ISBN 13
- 9780691127026
- Series
- Book 2 of 16: Princeton Studies in Complexity
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.
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