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

de John H. Miller, Scott E. Page

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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.… (mais)
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At first, I was a little disappointed by the lack of discussion of (code/pseudocode) implementation of models, frameworks, etc. (I think I went into this looking for a something more like an O'Reilly book.) But overall this was a very solid qualitative discussion of and around modeling, adaptive systems, etc. ( )
  dcunning11235 | Aug 12, 2023 |
This book provides a good introduction and explores several concrete models, using them to develop theory and point out strengths and weakness of various approaches. I would divide it into the following three sections:

Chapters 1-7 provide a slow and easy introduction to complexity and agent based models. Many interesting ideas are introduced but I had seen most of them in earlier books and found myself getting restless for something new. Since the book’s title had “introduction” in it I couldn’t fault the authors for taking the time to build up the concepts for people who had never been introduced to them before. I did enjoy the Buddhist “Eightfold Path” as applied to agent based models, where the authors describe the “Right View”, “Right Intention”, “Right Speech” etc . in terms of a good model. For instance “Right View” encompasses the information the agent receives for the world, “Right Speech” accounts for the information agents send to others and so on. Some of the analogies are a stretch as the authors point out, but it was a very nice way to think about modeling.

Chapters 8-12 cover more meaty examples and develop several “claims” (theorems) about the models. This was not quite what I was anticipating. These chapters are very practical for those working in the field and as the authors say later in the book “Great artists study the masters; so too must great modelers”. But I found the details of the models tedious and the mathematical formalism was in stark contrast to the first part of the book. Going from introductory material very accessible to a layperson to mathematical formalism, proof, Game Theory, Cellular Automata, and State Machines (in rule table format) is quite a jump. If you have been introduced to these subjects elsewhere then the material is not difficult, but for the authors to assume their readers will have this familiarity is expecting too much for an introductory text.

The book closes with two appendices. The first “An Open Agenda for Complex Adaptive Social Systems” provides a framework for the field and was full of all the interesting questions I was hoping the book would explore further. In my opinion it would have served as a great first chapter. The last appendix “Practices for Computational Models”, along with chapter 7, provided very practical and useful pointers for constructing computational models. ( )
2 vote gregfromgilbert | Nov 23, 2010 |
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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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