Complex Adaptive Systems: An Introduction to Computational Models of Social Life / Edition 1

by John H. Miller, Scott Page

Overview

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.

Product Details

ISBN-13:	9780691127026
Publisher:	Princeton University Press
Publication date:	03/25/2007
Series:	Princeton Studies in Complexity , #14
Edition description:	New Edition
Pages:	288
Sales rank:	521,341
Product dimensions:	6.00(w) x 9.25(h) x (d)

About the Author

John H. Miller is professor of economics and social sciences at Carnegie Mellon University. Scott E. Page is professor of complex systems, political science, and economics at the University of Michigan. He is the author of The Difference (Princeton).

Table of Contents

List of Figures     xiii
List of Tables     xv
Preface     xvii
Introduction     1
Introduction     3
Complexity in Social Worlds     9
The Standing Ovation Problem     10
What's the Buzz?     14
Stay Cool     14
Attack of the Killer Bees     15
Averaging Out Average Behavior     16
A Tale of Two Cities     17
Adding Complexity     20
New Directions     26
Complex Social Worlds Redux     27
Questioning Complexity     27
Preliminaries     33
Modeling     35
Models as Maps     36
A More Formal Approach to Modeling     38
Modeling Complex Systems     40
Modeling Modeling     42
On Emergence     44
A Theory of Emergence     46
Beyond Disorganized Complexity     48
Feedback and Organized Complexity     50
Computational Modeling     55
Computation as Theory     57
Theory versus Tools     59
Physics Envy: A Pseudo-Freudian Analysis     62
Computation and Theory     64
Computation in Theory     64
Computation as Theory     67
Objections to Computation as Theory     68
Computations Build in Their Results     69
Computations Lack Discipline     70
Computational Models Are Only Approximations to Specific Circumstances     71
Computational Models Are Brittle     72
Computational Models Are Hard to Test     73
Computational Models Are Hard to Understand     76
New Directions     76
Why Agent-Based Objects?     78
Flexibility versus Precision     78
Process Oriented     80
Adaptive Agents     81
Inherently Dynamic     83
Heterogeneous Agents and Asymmetry     84
Scalability     85
Repeatable and Recoverable     86
Constructive     86
Low Cost     87
Economic E. coli (E. coni?)     88
Models of Complex Adaptive Social Systems     91
A Basic Framework     93
The Eightfold Way     93
Right View     94
Right Intention     95
Right Speech     96
Right Action     96
Right Livelihood     97
Right Effort     98
Right Mindfulness     100
Right Concentration     101
Smoke and Mirrors: The Forest Fire Model     102
A Simple Model of Forest Fires     102
Fixed, Homogeneous Rules     102
Homogeneous Adaptation     104
Heterogeneous Adaptation     105
Adding More Intelligence: Internal Models     107
Omniscient Closure     108
Banks     109
Eight Folding into One     110
Conclusion     113
Complex Adaptive Social Systems in One Dimension     114
Cellular Automata     115
Social Cellular Automata     119
Socially Acceptable Rules     120
Majority Rules     124
The Zen of Mistakes in Majority Rule     128
The Edge of Chaos     129
Is There an Edge?     130
Computation at the Edge of Chaos     137
The Edge of Robustness     139
Social Dynamics     141
A Roving Agent     141
Segregation     143
The Beach Problem     146
City Formation     151
Networks      154
Majority Rule and Network Structures     158
Schelling's Segregation Model and Network Structures     163
Self-Organized Criticality and Power Laws     165
The Sand Pile Model     167
A Minimalist Sand Pile     169
Fat-Tailed Avalanches     171
Purposive Agents     175
The Forest Fire Model Redux     176
Criticality in Social Systems     177
Evolving Automata     178
Agent Behavior     178
Adaptation     180
A Taxonomy of 2 x 2 Games     185
Methodology     187
Results     189
Games Theory: One Agent, Many Games     191
Evolving Communication     192
Results     194
Furthering Communication     197
The Full Monty     198
Some Fundamentals of Organizational Decision Making     200
Organizations and Boolean Functions     201
Some Results     203
Do Organizations Just Find Solvable Problems?     206
Imperfection     207
Future Directions     210
Conclusions     211
Social Science in Between     213
Some Contributions      214
The Interest in Between     218
In between Simple and Strategic Behavior     219
In between Pairs and Infinities of Agents     221
In between Equilibrium and Chaos     222
In between Richness and Rigor     223
In between Anarchy and Control     225
Here Be Dragons     225
Epilogue     227
Interest in Between     227
Social Complexity     228
The Faraway Nearby     230
Appendixes
An Open Agenda For Complex Adaptive Social Systems     231
Whither Complexity     231
What Does it Take for a System to Exhibit Complex Behavior?     233
Is There an Objective Basis for Recognizing Emergence and Complexity?     233
Is There a Mathematics of Complex Adaptive Social Systems?     234
What Mechanisms Exist for Tuning the Performance of Complex Systems?     235
Do Productive Complex Systems Have Unusual Properties?     235
Do Social Systems Become More Complex over Time     236
What Makes a System Robust?     236
Causality in Complex Systems?     237
When Does Coevolution Work?     237
When Does Updating Matter?     238
When Does Heterogeneity Matter?     238
How Sophisticated Must Agents Be Before They Are Interesting?     239
What Are the Equivalence Classes of Adaptive Behavior?     240
When Does Adaptation Lead to Optimization and Equilibrium?     241
How Important Is Communication to Complex Adaptive Social Systems?     242
How Do Decentralized Markets Equilibrate?     243
When Do Organizations Arise?     243
What Are the Origins of Social Life?     244
Practices for Computational Modeling     245
Keep the Model Simple     246
Focus on the Science, Not the Computer     246
The Old Computer Test     247
Avoid Black Boxes     247
Nest Your Models     248
Have Tunable Dials     248
Construct Flexible Frameworks     249
Create Multiple Implementations     249
Check the Parameters     250
Document Code     250
Know the Source of Random Numbers     251
Beware of Debugging Bias     251
Write Good Code     251
Avoid False Precision     252
Distribute Your Code     253
Keep a Lab Notebook     253
Prove Your Results      253
Reward the Right Things     254
Bibliography     255
Index     261

What People are Saying About This

Arrow

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

Elinor Ostrom

This is a wonderful book that will be read by graduate students, faculty, and policymakers. The authors write in an extraordinarily clear manner about topics that are very technical and difficult for many people. I sat down to begin thumbing through and found myself deeply engaged.
— Elinor Ostrom, author of "Understanding Institutional Diversity"

From the Publisher

"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

"In Complex Adaptive Systems, two masters of this burgeoning field provide a highly readable and novel restatement of the logic of social interactions, linking individually based micro processes to macrosocial outcomes, ranging from Adam Smith's invisible hand to Thomas Schelling's models of standing ovations. The book combines the vision of a new Santa Fe school of computational, social, and behavioral science with essential 'how to' advice for apprentice modelers."—Samuel Bowles, author of Microeconomics: Behavior, Institutions, Evolution

"This is a wonderful book that will be read by graduate students, faculty, and policymakers. The authors write in an extraordinarily clear manner about topics that are very technical and difficult for many people. I sat down to begin thumbing through and found myself deeply engaged."—Elinor Ostrom, author of Understanding Institutional Diversity

Samuel Bowles

In Complex Adaptive Systems, two masters of this burgeoning field provide a highly readable and novel restatement of the logic of social interactions, linking individually based micro processes to macrosocial outcomes, ranging from Adam Smith's invisible hand to Thomas Schelling's models of standing ovations. The book combines the vision of a new Santa Fe school of computational, social, and behavioral science with essential 'how to' advice for apprentice modelers.
— Samuel Bowles, author of "Microeconomics: Behavior, Institutions, Evolution"

Editorial Reviews

"In Complex Adaptive Systems, two masters of this burgeoning field provide a highly readable and novel restatement of the logic of social interactions, linking individually based micro processes to macrosocial outcomes, ranging from Adam Smith's invisible hand to Thomas Schelling's models of standing ovations. The book combines the vision of a new Santa Fe school of computational, social, and behavioral science with essential 'how to' advice for apprentice modelers."--Samuel Bowles, author of Microeconomics: Behavior, Institutions, Evolution

"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

"This is a wonderful book that will be read by graduate students, faculty, and policymakers. The authors write in an extraordinarily clear manner about topics that are very technical and difficult for many people. I sat down to begin thumbing through and found myself deeply engaged."--Elinor Ostrom, author of Understanding Institutional Diversity

From the Publisher