Complex Adaptive Systems: An Introduction to Computational Models of Social Life: An Introduction to Computational Models of Social Life
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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Complexity in Social Worlds
Why AgentBased Objects?
When Does Adaptation Lead to Optimization and Equilibrium?
How Important Is Communication to Complex Adaptive Social Systems?
How Do Decentralized Markets Equilibrate?
What Are the Origins of Social Life?
B Practices for Computational Modeling
Keep the Model Simple
The Old Computer Test
Nest Your Models
Models of Complex Adaptive
Complex Adaptive Social Systems in One Dimension
Some Fundamentals of Organizational Decision Making
Social Science in Between
How Sophisticated Must Agents Be Before They Are Interesting?
What Are the Equivalence Classes of Adaptive Behavior?
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Complex Adaptive Systems: An Introduction to Computational Models of Social Life
John Howard Miller,Scott E. Page
No preview available - 2007