9780691127026-0691127026-Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity, 14)

Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity, 14)

ISBN-13: 9780691127026
ISBN-10: 0691127026
Author: John H. Miller, Scott Page
Publication date: 2007
Publisher: Princeton University Press
Format: Paperback 288 pages
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ISBN-13: 9780691127026
ISBN-10: 0691127026
Author: John H. Miller, Scott Page
Publication date: 2007
Publisher: Princeton University Press
Format: Paperback 288 pages

Summary

Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity, 14) (ISBN-13: 9780691127026 and ISBN-10: 0691127026), written by authors John H. Miller, Scott Page, was published by Princeton University Press in 2007. With an overall rating of 3.9 stars, it's a notable title among other History & Philosophy (Applied, Mathematics, System Theory, Physics, Social Sciences, Sociology) books. You can easily purchase or rent Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity, 14) (Paperback) from BooksRun, along with many other new and used History & Philosophy books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $5.05.

Description

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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