product iamge

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

This document was uploaded by one of our users. The uploader already confirmed that they had the permission to publish it. If you are author/publisher or own the copyright of this documents, please report to us by using this DMCA report form.

Download
Search on Amazon

Simply click on the Download Book button.

Yes, Book downloads on Ebookily are 100% Free.

Sometimes the book is free on Amazon As well, so go ahead and hit "Search on Amazon"

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.

Author(s): John H. Miller, Scott E. Page
Series: Princeton Studies in Complexity
Edition: illustrated edition
Publisher: Princeton University Press
Year: 2007

Language: English
Pages: 284

Cover
......Page 0
Contents
......Page 7
Part I Introduction......Page 21
1 Introduction......Page 23
2 Complexity in Social Worlds......Page 29
2.1 The Standing Ovation Problem......Page 30
2.2.1 Stay Cool......Page 34
2.2.2 Attack of the Killer Bees......Page 35
2.2.3 Averaging Out Average Behavior......Page 36
2.3 A Tale of Two Cities......Page 37
2.3.1 Adding Complexity......Page 40
2.4 New Directions......Page 46
2.5.1 Questioning Complexity......Page 47
Part II Preliminaries......Page 53
3 Modeling......Page 55
3.1 Models as Maps......Page 56
3.2 A More Formal Approach to Modeling......Page 58
3.3 Modeling Complex Systems......Page 60
3.4 Modeling Modeling......Page 62
4 On Emergence......Page 64
4.1 A Theory of Emergence......Page 66
4.2 Beyond Disorganized Complexity......Page 68
4.2.1 Feedback and Organized Complexity......Page 70
Part III Computational Modeling......Page 75
5 Computation as Theory......Page 77
5.1 Theory versus Tools......Page 79
5.1.1 Physics Envy: A Pseudo-Freudian Analysis......Page 82
5.2.1 Computation in Theory......Page 84
5.2.2 Computation as Theory......Page 87
5.3 Objections to Computation as Theory......Page 88
5.3.1 Computations Build in Their Results......Page 89
5.3.2 Computations Lack Discipline......Page 90
5.3.3 Computational Models Are Only Approximations to Specific Circumstances......Page 91
5.3.4 Computational Models Are Brittle......Page 92
5.3.5 Computational Models Are Hard to Test......Page 93
5.4 New Directions......Page 96
6.1 Flexibility versus Precision......Page 98
6.2 Process Oriented......Page 100
6.3 Adaptive Agents......Page 101
6.4 Inherently Dynamic......Page 103
6.5 Heterogeneous Agents and Asymmetry......Page 104
6.6 Scalability......Page 105
6.8 Constructive......Page 106
6.9 Low Cost......Page 107
6.10 Economic E. coli (E. coni?)......Page 108
Part IV Models of Complex Adaptive Social Systems......Page 111
7.1 The Eightfold Way......Page 113
7.1.1 Right View......Page 114
7.1.2 Right Intention......Page 115
7.1.4 Right Action......Page 116
7.1.5 Right Livelihood......Page 117
7.1.6 Right Effort......Page 118
7.1.7 Right Mindfulness......Page 120
7.1.8 Right Concentration......Page 121
7.2.2 Fixed, Homogeneous Rules......Page 122
7.2.3 Homogeneous Adaptation......Page 124
7.2.4 Heterogeneous Adaptation......Page 125
7.2.5 Adding More Intelligence: Internal Models......Page 127
7.2.6 Omniscient Closure......Page 128
7.2.7 Banks......Page 129
7.3 Eight Folding into One......Page 130
7.4 Conclusion......Page 133
8 Complex Adaptive Social Systems in One Dimension......Page 134
8.1 Cellular Automata......Page 135
8.2 Social Cellular Automata......Page 139
8.2.1 Socially Acceptable Rules......Page 140
8.3 Majority Rules......Page 144
8.3.1 The Zen of Mistakes in Majority Rule......Page 148
8.4 The Edge of Chaos......Page 149
8.4.1 Is There an Edge?......Page 150
8.4.2 Computation at the Edge of Chaos......Page 157
8.4.3 The Edge of Robustness......Page 159
9.1 A Roving Agent......Page 161
9.2 Segregation......Page 163
9.3 The Beach Problem......Page 166
9.4 City Formation......Page 171
9.5 Networks......Page 174
9.5.1 Majority Rule and Network Structures......Page 178
9.5.2 Schelling’s Segregation Model and Network Structures......Page 183
9.6 Self-Organized Criticality and Power Laws......Page 185
9.6.1 The Sand Pile Model......Page 187
9.6.2 A Minimalist Sand Pile......Page 189
9.6.3 Fat-Tailed Avalanches......Page 191
9.6.4 Purposive Agents......Page 195
9.6.5 The Forest Fire Model Redux......Page 196
9.6.6 Criticality in Social Systems......Page 197
10.1 Agent Behavior......Page 198
10.2 Adaptation......Page 200
10.3 A Taxonomy of 2 × 2 Games......Page 205
10.3.1 Methodology......Page 207
10.3.2 Results......Page 209
10.4 Games Theory: One Agent, Many Games......Page 211
10.5 Evolving Communication......Page 212
10.5.1 Results......Page 214
10.5.2 Furthering Communication......Page 217
10.6 The Full Monty......Page 218
11 Some Fundamentals of Organizational Decision Making......Page 220
11.1 Organizations and Boolean Functions......Page 221
11.2 Some Results......Page 223
11.3 Do Organizations Just Find Solvable Problems?......Page 226
11.3.1 Imperfection......Page 227
11.4 Future Directions......Page 230
Part V Conclusions......Page 231
12 Social Science in Between......Page 233
12.1 Some Contributions......Page 234
12.2 The Interest in Between......Page 238
12.2.1 In between Simple and Strategic Behavior......Page 239
12.2.2 In between Pairs and Infinities of Agents......Page 241
12.2.3 In between Equilibrium and Chaos......Page 242
12.2.4 In between Richness and Rigor......Page 243
12.3 Here Be Dragons......Page 245
The Interest in Between......Page 247
Social Complexity......Page 248
The Faraway Nearby......Page 250
A.1 Whither Complexity......Page 251
A.3 Is There an Objective Basis for Recognizing Emergence and Complexity?......Page 253
A.4 Is There a Mathematics of Complex Adaptive Social Systems?......Page 254
A.6 Do Productive Complex Systems Have Unusual Properties?......Page 255
A.8 What Makes a System Robust?......Page 256
A.10 When Does Coevolution Work?......Page 257
A.12 When Does Heterogeneity Matter?......Page 258
A.13 How Sophisticated Must Agents Be Before They Are Interesting?......Page 259
A.14 What Are the Equivalence Classes of Adaptive Behavior?......Page 260
A.15 When Does Adaptation Lead to Optimization and Equilibrium?......Page 261
A.16 How Important Is Communication to Complex Adaptive Social Systems?......Page 262
A.18 When Do Organizations Arise?......Page 263
A.19 What Are the Origins of Social Life?......Page 264
B Practices for Computational Modeling......Page 265
B.2 Focus on the Science, Not the Computer......Page 266
B.4 Avoid Black Boxes......Page 267
B.6 Have Tunable Dials......Page 268
B.8 Create Multiple Implementations......Page 269
B.10 Document Code......Page 270
B.13 Write Good Code......Page 271
B.14 Avoid False Precision......Page 272
B.17 Prove Your Results......Page 273
B.18 Reward the Right Things......Page 274
Bibliography......Page 275
Index......Page 281