Complex Adaptive Systems

An Introduction to Computational Models of Social Life
Erscheinungsjahr 2007
ISBN: 978-0-691-12702-6
Verlag: Princeton University Press

Buch, Englisch, 284 Seiten, Format (B × H): 154 mm x 237 mm, Gewicht: 425 g

Reihe: Princeton Studies in Complexity

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.

Autoren/Hrsg.

Miller, John H.

Page, Scott E.

Fachgebiete

• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Demographie, Demoskopie
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie
• Mathematik | Informatik Mathematik Geometrie Dynamische Systeme
• Interdisziplinäres Wissenschaften Wissenschaften Interdisziplinär Wirtschafts- und Sozialwissenschaften

Inhaltsverzeichnis

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:

Über Autor(innen)

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).