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

by John H. Miller and Scott E. Page Princeton University Press
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Pbk 288 pages
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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.

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

List of Figures xiii

List of Tables xv

Preface xvii

Part I: Introduction 1

Chapter 1: Introduction 3

Chapter 2: Complexity in Social Worlds 9

2.1 The Standing Ovation Problem 10

2.2 What's the Buzz? 14

2.2.1 Stay Cool 14

2.2.2 Attack of the Killer Bees 15

2.2.3 Averaging Out Average Behavior 16

2.3 A Tale of Two Cities 17

2.3.1 Adding Complexity 20

2.4 New Directions 26

2.5 Complex Social Worlds Redux 27

2.5.1 Questioning Complexity 27

Part II: Preliminaries 33

Chapter 3: Modeling 35

3.1 Models as Maps 36

3.2 A More Formal Approach to Modeling 38

3.3 Modeling Complex Systems 40

3.4 Modeling Modeling 42

Chapter 4: On Emergence 44

4.1 A Theory of Emergence 46

4.2 Beyond Disorganized Complexity 48

4.2.1 Feedback and Organized Complexity 50

Part III: Computational Modeling 55

Chapter 5: Computation as Theory 57

5.1 Theory versus Tools 59

5.1.1 Physics Envy: A Pseudo-Freudian Analysis 62

5.2 Computation and Theory 64

5.2.1 Computation in Theory 64

5.2.2 Computation as Theory 67

5.3 Objections to Computation as Theory 68

5.3.1 Computations Build in Their Results 69

5.3.2 Computations Lack Discipline 70

5.3.3 Computational Models Are Only Approximations to Specific Circumstances 71

5.3.4 Computational Models Are Brittle 72

5.3.5 Computational Models Are Hard to Test 73

5.3.6 Computational Models Are Hard to Understand 76

5.4 New Directions 76

Chapter 6: Why Agent-Based Objects? 78

6.1 Flexibility versus Precision 78

6.2 Process Oriented 80

6.3 Adaptive Agents 81

6.4 Inherently Dynamic 83

6.5 Heterogeneous Agents and Asymmetry 84

6.6 Scalability 85

6.7 Repeatable and Recoverable 86

6.8 Constructive 86

6.9 Low Cost 87

6.10 Economic E. coli (E. coni?) 88

Part IV: Models of Complex Adaptive Social Systems 91

Chapter 7: A Basic Framework 93

7.1 The Eightfold Way 93

7.1.1 Right View 94

7.1.2 Right Intention 95

7.1.3 Right Speech 96

7.1.4 Right Action 96

7.1.5 Right Livelihood 97

7.1.6 Right Effort 98

7.1.7 Right Mindfulness 100

7.1.8 Right Concentration 101

7.2 Smoke and Mirrors: The Forest Fire Model 102

7.2.1 A Simple Model of Forest Fires 102

7.2.2 Fixed, Homogeneous Rules 102

7.2.3 Homogeneous Adaptation 104

7.2.4 Heterogeneous Adaptation 105

7.2.5 Adding More Intelligence: Internal Models 107

7.2.6 Omniscient Closure 108

7.2.7 Banks 109

7.3 Eight Folding into One 110

7.4 Conclusion 113

Chapter 8: Complex Adaptive Social Systems in One Dimension 114

8.1 Cellular Automata 115

8.2 Social Cellular Automata 119

8.2.1 Socially Acceptable Rules 120

8.3 Majority Rules 124

8.3.1 The Zen of Mistakes in Majority Rule 128

8.4 The Edge of Chaos 129

8.4.1 Is There an Edge? 130

8.4.2 Computation at the Edge of Chaos 137

8.4.3 The Edge of Robustness 139

Chapter 9: Social Dynamics 141

9.1 A Roving Agent 141

9.2 Segregation 143

9.3 The Beach Problem 146

9.4 City Formation 151

9.5 Networks 154

9.5.1 Majority Rule and Network Structures 158

9.5.2 Schelling's Segregation Model and Network Structures 163

9.6 Self-Organized Criticality and Power Laws 165

9.6.1 The Sand Pile Model 167

9.6.2 A Minimalist Sand Pile 169

9.6.3 Fat-Tailed Avalanches 171

9.6.4 Purposive Agents 175

9.6.5 The Forest Fire Model Redux 176

9.6.6 Criticality in Social Systems 177

Chapter 10: Evolving Automata 178

10.1 Agent Behavior 178

10.2 Adaptation 180

10.3 A Taxonomy of 2 x 2 Games 185

10.3.1 Methodology 187

10.3.2 Results 189

10.4 Games Theory: One Agent, Many Games 191

10.5 Evolving Communication 192

10.5.1 Results 194

10.5.2 Furthering Communication 197

10.6 The Full Monty 198

Chapter 11: Some Fundamentals of Organizational Decision Making 200

11.1 Organizations and Boolean Functions 201

11.2 Some Results 203

11.3 Do Organizations Just Find Solvable Problems? 206

11.3.1 Imperfection 207

11.4 Future Directions 210

Part V: Conclusions 211

Chapter 12: Social Science in Between 213

12.1 Some Contributions 214

12.2 The Interest in Between 218

12.2.1 In between Simple and Strategic Behavior 219

12.2.2 In between Pairs and Infinities of Agents 221

12.2.3 In between Equilibrium and Chaos 222

12.2.4 In between Richness and Rigor 223

12.2.5 In between Anarchy and Control 225

12.3 Here Be Dragons 225

Epilogue 227

The Interest in Between 227

Social Complexity 228

The Faraway Nearby 230


A An Open Agenda For Complex Adaptive Social Systems 231

A.1 Whither Complexity 231

A.2 What Does it Take for a System to Exhibit Complex
Behavior? 233

A.3 Is There an Objective Basis for Recognizing Emergence and
Complexity? 233

A.4 Is There a Mathematics of Complex Adaptive Social Systems? 234

A.5 What Mechanisms Exist for Tuning the Performance of
Complex Systems? 235

A.6 Do Productive Complex Systems Have Unusual Properties? 235

A.7 Do Social Systems Become More Complex over Time 236

A.8 What Makes a System Robust? 236

A.9 Causality in Complex Systems? 237

A.10 When Does Coevolution Work? 237

A.11 When Does Updating Matter? 238

A.12 When Does Heterogeneity Matter? 238

A.13 How Sophisticated Must Agents Be Before They Are Interesting? 239

A.14 What Are the Equivalence Classes of Adaptive Behavior? 240

A.15 When Does Adaptation Lead to Optimization and Equilibrium? 241

A.16 How Important Is Communication to Complex Adaptive Social Systems? 242

A.17 How Do Decentralized Markets Equilibrate? 243

A.18 When Do Organizations Arise? 243

A.19 What Are the Origins of Social Life? 244

B Practices for Computational Modeling 245

B.1 Keep the Model Simple 246

B.2 Focus on the Science, Not the Computer 246

B.3 The Old Computer Test 247

B.4 Avoid Black Boxes 247

B.5 Nest Your Models 248

B.6 Have Tunable Dials 248

B.7 Construct Flexible Frameworks 249

B.8 Create Multiple Implementations 249

B.9 Check the Parameters 250

B.10 Document Code 250

B.11 Know the Source of Random Numbers 251

B.12 Beware of Debugging Bias 251

B.13 Write Good Code 251

B.14 Avoid False Precision 252

B.15 Distribute Your Code 253

B.16 Keep a Lab Notebook 253

B.17 Prove Your Results 253

B.18 Reward the Right Things 254

Bibliography 255

Index 261

This unique, interesting, and stimulating book shoehorns the whole of Russian history into a single long essay, one that is argued very forcefully and written with remarkable clarity and verve. Reginald Zelnik, University of California, Berkeley, author of 'Law and Disorder on the Narova River' This is a stimulating and timely essay, which, as intended, is provocative and potentially controversial at every turn. Simon Franklin, Clare College, University of Cambridge, coauthor of 'The Emergence of Rus' 750-1200' If half a millennium of Russian history is to be distilled into a hundred pages of text, one has to have a strong thesis. Poe does. . . If those who disagree can offer a counterargument as compact, vigorous, and accessible as Poe's, the rest of us will greatly benefit. Foreign Affairs Condensing 1,400 years of history into 100 well-argued pages is a remarkable feat, one Poe accomplishes in terse but powerfully stated prose. . . . Poe effectively commits to his chosen path of navigation and distills his observations and vast knowledge into a clear and well-presented theory. The author deserves credit for taking on the gutsy task of re-educating that he sees as a misinformed public with humility intact, an achievement that is a testament to the purity of his intent. Gabriella Gershenson San Francisco Chronicle Students will find Poe an able provocateur of debate. Booklist This slim volume offers a sweeping yet cogent and highly stimulating reinterpretation of the entire course of Russian history from the time of the earliest settlers in Russian lands to the collapse of the Soviet Union. While intended for general readers, the author's views are firmly grounded in recent scholarship. Choice The task of compressing the whole history of Russia into a hundred easy-to-read pages would be a hard challenge for any serious historian, but the proposition of building and testing in the same space an innovative concept of what Russia is about might seem beyond possible. This neat book by Poe, which many readers would find difficult to put down before turning the last page, is the tangible proof that such a task can indeed by accomplished--and with astounding ease. Pavel Baev Journal of Peace Research The thesis of this volume is that as late as the fifteenth century Russia was largely irrelevant to world history, that it became a noteworthy player in the sixteenth century, and that it remained so most of the time until 1991. Richard Hellie Journal of Modern History
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).