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

by John H. Miller (Author), Scott E. Page (Author)

Editorial Reviews

Review
"Shows that computational modeling is slowly beginning to take root in the social sciences." -- Philip Ball, Nature

Review
The use of computational, especially agent-based, models has already shown its value in illuminating the study of economic and other social processes. Miller and Page have written an orientation to this field that is a model of motivation and insight, making clear the underlying thinking and illustrating it by varied and thoughtful examples. It conveys with remarkable clarity the essentials of the complex systems approach to the embarking researcher.
(Kenneth J. Arrow, winner of the Nobel Prize in economics )

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Product Details

• Paperback: 284 pages
• Publisher: Princeton University Press; illustrated edition edition (March 5, 2007)
• Language: English
• ISBN-10: 0691127026
• ISBN-13: 978-0691127026
• Product Dimensions: 9.2 x 6.1 x 0.8 inches
• Shipping Weight: 15.2 ounces (View shipping rates and policies)
• Average Customer Review: 4.4 out of 5 stars See all reviews (8 customer reviews)
• Amazon.com Sales Rank: #33,258 in Books (See Bestsellers in Books)

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Customer Reviews

Most Helpful Customer Reviews

57 of 59 people found the following review helpful:

5.0 out of 5 stars The Emergence of Convergence , August 3, 2007

By	Vincent Matossian (Piscataway, NJ United States) - See all my reviews (REAL NAME)

At the time of writing this review, this book isn't searchable through Amazon, that's too bad because if you're reading the reviews wondering if it's worth buying, just browsing through any page from the intro or appendix B would clearly resolve any remnant hesitation. This book is a must have for anyone even remotely interested in complex adaptive systems. Scott Page and John Miller dress the landscape and state of the art of computational social science, the issues are motivated from the ground up and the existing approaches to resolve them explicitly detailed, yet using clear and jargon free language. For example, descriptions of the many concepts repeatedly used in the scientific method (of CAS et al) such as ergodicity or optimization theory are refreshing and insightful, simply stuff you don't get from textbooks, but rather that one would learn over years of experience doing.

In summary, the authors are handing us an expert summary of literature and developments of a complex field in a concise, fun and delightful read, it would be a shame to miss it.

34 of 38 people found the following review helpful:

4.0 out of 5 stars A Gentle and Insightful Introduction to Complexity, December 1, 2007

By	Herbert Gintis (Northampton, MA USA) - See all my reviews

Living systems are generally complex, dynamic adaptive systems with emergent properties that analytical models attending only to the local interactions of the system fail to capture. We must complement the standard analytical methods of physics, biology, and economics by additional mathematical tools, such as agent-based simulation and network theory.

A complex system consists of a large population of similar entities (e.g., human individuals) who interact through regularized channels (e.g., networks, markets, social institutions) with significant stochastic elements, without a system of centralized organization and control (i.e., if there is a state, it controls only a fraction of all social interactions, and itself is a complex system). A complex system is adaptive if it evolves through some evolutionary (genetic, cultural, agent-based silicon, or other) process of hereditary reproduction, mutation, and selection.. Characterizing a system as complex adaptive does not explain its operation, and does not solve any problems. However, it suggests that certain modeling tools are likely to be effective that have little use in a non-complex system.

Such novel research tools are needed because a complex adaptive system generally has emergent properties that cannot be analytically derived from its component parts. The stunning success of modern physics and chemistry lies in their ability to avoid or strictly limit emergence. Indeed, the experimental method in natural science is to create highly simplified laboratory conditions, under which modeling becomes analytically tractable. Physics is no more effective than economics or biology in analyzing complex real-world phenomena in situ.. The various branches of engineering (electrical, chemical, mechanical) are effective because they recreate in everyday life artificially controlled, non-complex, non-adaptive, environments that can directly apply the discoveries of physics and chemistry. This option is generally not open to most behavioral scientists, who rarely have the opportunity of ``engineering'' social institutions and cultures.

Miller and Page stress that complex systems cannot be properly modeled using the statistical and mathematical tools associated with differentiable manifolds and normal statistical distributions. Rather, complex phenomena exhibit power law behavior in which statistical distributions have "fat tails" that lead to considerable activity far from the distributions central tendency. A rather stunning example, discussed in Chapter 9, is the size distribution of wars in the world occurring between 1820 and 1943. When the number of deaths in a war (a good measure of the size of the war) is 10 to the power n, the number of wars with this size is about 2 x 3 to the power 7-n.

Miller and Page do a find job of making complexity analysis accessible to the non-expert, without overwhelming the reader with specialized aspects of agent-based modeling or dynamical systems. They provide an exciting stepping-off point for detailed studies in particular disciplines.

6 of 7 people found the following review helpful:

5.0 out of 5 stars very good introduction to the subject, July 23, 2008

By	F. Barbieri (Ribeirão Preto, SP Brazil) - See all my reviews (REAL NAME)

A nice introduction material. You will learn how complex phenomena are currently studied . I will use this book as an intro material to complex systems in my economics course.
My only complain is that the book scarcelly discuss aplications in social sciences!!! I have to use specific articles with applications for that. the author should supress the subtitle. but it is still an excellent book.