Complex adaptive systems 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 challen...
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| Hlavní autoři: | , |
|---|---|
| Médium: | E-kniha Kniha |
| Jazyk: | angličtina |
| Vydáno: |
Princeton, N.J
Princeton University Press
2007
Princeton Univ. Press |
| Vydání: | STU - Student edition |
| Edice: | Princeton Studies in Complexity |
| Témata: | |
| ISBN: | 9780691127026, 0691130965, 9780691130965, 0691127026, 9781400835522, 1400835526 |
| On-line přístup: | Získat plný text |
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- Complex adaptive systems: an introduction to computational models of social life -- Contents -- Part I: Introduction -- Chapter 1: Introduction -- Chapter 2: Complexity in Social Worlds -- Part II: Preliminaries -- Chapter 3: Modeling -- Chapter 4: On Emergence -- Part III: Computational Modeling -- Chapter 5: Computation as Theory -- Chapter 6: Why Agent-Based Objects? -- Part IV: Models of Complex Adaptive Social Systems -- Chapter 7: A Basic Framework -- Chapter 8: Complex Adaptive Social Systems in One Dimension -- Chapter 9: Social Dynamics -- Chapter 10: Evolving Automata -- Chapter 11: Some Fundamentals of Organizational Decision Making -- Part V: Conclusions -- Chapter 12: Social Science in Between -- Epilogue -- Appendixes A: An Open Agenda For Complex Adaptive Social Systems -- Appendixes B: Practices for Computational Modeling -- Bibliography -- Index
- Front Matter Table of Contents List of Figures List of Tables Preface CHAPTER 1: Introduction CHAPTER 2: Complexity in Social Worlds CHAPTER 3: Modeling CHAPTER 4: On Emergence CHAPTER 5: Computation as Theory CHAPTER 6: Why Agent-Based Objects? CHAPTER 7: A Basic Framework CHAPTER 8: Complex Adaptive Social Systems in One Dimension CHAPTER 9: Social Dynamics CHAPTER 10: Evolving Automata CHAPTER 11: Some Fundamentals of Organizational Decision Making CHAPTER 12: Social Science in Between Epilogue APPENDIX A APPENDIX B Bibliography Index
- Series Page, Title Page, Copyright, Dedication Contents Figures Tables Preface Part I Introduction 1 Introduction 2 Complexity in Social Worlds Part II Preliminaries 3 Modeling 4 On Emergence Part III Computational Modeling 5 Computation as Theory 6 Why Agent-Based Objects? Part IV Models of Complex Adaptive Social Systems 7 A Basic Framework 8 Complex Adaptive Social Systems in One Dimension 9 Social Dynamics 10 Evolving Automata 11 Some Fundamentals of Organizational Decision Making Part V Conclusions 12 Social Science in Between Epilogue Appendix A: An Open Agenda For Complex Adaptive Social Systems Appendix B: Practices for Computational Modeling Bibliography Index
- 12.2.3 In between Equilibrium and Chaos -- 12.2.4 In between Richness and Rigor -- 12.2.5 In between Anarchy and Control -- 12.3 Here Be Dragons -- Epilogue -- The Interest in Between -- Social Complexity -- The Faraway Nearby -- Appendixes A An Open Agenda For Complex Adaptive Social Systems -- A.1 Whither Complexity -- A.2 What Does it Take for a System to Exhibit Complex Behavior? -- A.3 Is There an Objective Basis for Recognizing Emergence and Complexity? -- A.4 Is There a Mathematics of Complex Adaptive Social Systems? -- A.5 What Mechanisms Exist for Tuning the Performance of Complex Systems? -- A.6 Do Productive Complex Systems Have Unusual Properties? -- A.7 Do Social Systems Become More Complex over Time -- A.8 What Makes a System Robust? -- A.9 Causality in Complex Systems? -- A.10 When Does Coevolution Work? -- A.11 When Does Updating Matter? -- A.12 When Does Heterogeneity Matter? -- A.13 How Sophisticated Must Agents Be Before They Are Interesting? -- A.14 What Are the Equivalence Classes of Adaptive Behavior? -- A.15 When Does Adaptation Lead to Optimization and Equilibrium? -- A.16 How Important Is Communication to Complex Adaptive Social Systems? -- A.17 How Do Decentralized Markets Equilibrate? -- A.18 When Do Organizations Arise? -- A.19 What Are the Origins of Social Life? -- B Practices for Computational Modeling -- B.1 Keep the Model Simple -- B.2 Focus on the Science, Not the Computer -- B.3 The Old Computer Test -- B.4 Avoid Black Boxes -- B.5 Nest Your Models -- B.6 Have Tunable Dials -- B.7 Construct Flexible Frameworks -- B.8 Create Multiple Implementations -- B.9 Check the Parameters -- B.10 Document Code -- B.11 Know the Source of Random Numbers -- B.12 Beware of Debugging Bias -- B.13 Write Good Code -- B.14 Avoid False Precision -- B.15 Distribute Your Code -- B.16 Keep a Lab Notebook -- B.17 Prove Your Results
- Intro -- Contents -- Part I Introduction -- 1 Introduction -- 2 Complexity in Social Worlds -- 2.1 The Standing Ovation Problem -- 2.2 What's the Buzz? -- 2.2.1 Stay Cool -- 2.2.2 Attack of the Killer Bees -- 2.2.3 Averaging Out Average Behavior -- 2.3 A Tale of Two Cities -- 2.3.1 Adding Complexity -- 2.4 New Directions -- 2.5 Complex Social Worlds Redux -- 2.5.1 Questioning Complexity -- Part II Preliminaries -- 3 Modeling -- 3.1 Models as Maps -- 3.2 A More Formal Approach to Modeling -- 3.3 Modeling Complex Systems -- 3.4 Modeling Modeling -- 4 On Emergence -- 4.1 A Theory of Emergence -- 4.2 Beyond Disorganized Complexity -- 4.2.1 Feedback and Organized Complexity -- Part III Computational Modeling -- 5 Computation as Theory -- 5.1 Theory versus Tools -- 5.1.1 Physics Envy: A Pseudo-Freudian Analysis -- 5.2 Computation and Theory -- 5.2.1 Computation in Theory -- 5.2.2 Computation as Theory -- 5.3 Objections to Computation as Theory -- 5.3.1 Computations Build in Their Results -- 5.3.2 Computations Lack Discipline -- 5.3.3 Computational Models Are Only Approximations to Specific Circumstances -- 5.3.4 Computational Models Are Brittle -- 5.3.5 Computational Models Are Hard to Test -- 5.3.6 Computational Models Are Hard to Understand -- 5.4 New Directions -- 6 Why Agent-Based Objects? -- 6.1 Flexibility versus Precision -- 6.2 Process Oriented -- 6.3 Adaptive Agents -- 6.4 Inherently Dynamic -- 6.5 Heterogeneous Agents and Asymmetry -- 6.6 Scalability -- 6.7 Repeatable and Recoverable -- 6.8 Constructive -- 6.9 Low Cost -- 6.10 Economic E. coli (E. coni?) -- Part IV Models of Complex Adaptive Social Systems -- 7 A Basic Framework -- 7.1 The Eightfold Way -- 7.1.1 Right View -- 7.1.2 Right Intention -- 7.1.3 Right Speech -- 7.1.4 Right Action -- 7.1.5 Right Livelihood -- 7.1.6 Right Effort -- 7.1.7 Right Mindfulness -- 7.1.8 Right Concentration
- 7.2 Smoke and Mirrors: The Forest Fire Model -- 7.2.1 A Simple Model of Forest Fires -- 7.2.2 Fixed, Homogeneous Rules -- 7.2.3 Homogeneous Adaptation -- 7.2.4 Heterogeneous Adaptation -- 7.2.5 Adding More Intelligence: Internal Models -- 7.2.6 Omniscient Closure -- 7.2.7 Banks -- 7.3 Eight Folding into One -- 7.4 Conclusion -- 8 Complex Adaptive Social Systems in One Dimension -- 8.1 Cellular Automata -- 8.2 Social Cellular Automata -- 8.2.1 Socially Acceptable Rules -- 8.3 Majority Rules -- 8.3.1 The Zen of Mistakes in Majority Rule -- 8.4 The Edge of Chaos -- 8.4.1 Is There an Edge? -- 8.4.2 Computation at the Edge of Chaos -- 8.4.3 The Edge of Robustness -- 9 Social Dynamics -- 9.1 A Roving Agent -- 9.2 Segregation -- 9.3 The Beach Problem -- 9.4 City Formation -- 9.5 Networks -- 9.5.1 Majority Rule and Network Structures -- 9.5.2 Schelling's Segregation Model and Network Structures -- 9.6 Self-Organized Criticality and Power Laws -- 9.6.1 The Sand Pile Model -- 9.6.2 A Minimalist Sand Pile -- 9.6.3 Fat-Tailed Avalanches -- 9.6.4 Purposive Agents -- 9.6.5 The Forest Fire Model Redux -- 9.6.6 Criticality in Social Systems -- 10 Evolving Automata -- 10.1 Agent Behavior -- 10.2 Adaptation -- 10.3 A Taxonomy of 2 × 2 Games -- 10.3.1 Methodology -- 10.3.2 Results -- 10.4 Games Theory: One Agent, Many Games -- 10.5 Evolving Communication -- 10.5.1 Results -- 10.5.2 Furthering Communication -- 10.6 The Full Monty -- 11 Some Fundamentals of Organizational Decision Making -- 11.1 Organizations and Boolean Functions -- 11.2 Some Results -- 11.3 Do Organizations Just Find Solvable Problems? -- 11.3.1 Imperfection -- 11.4 Future Directions -- Part V Conclusions -- 12 Social Science in Between -- 12.1 Some Contributions -- 12.2 The Interest in Between -- 12.2.1 In between Simple and Strategic Behavior -- 12.2.2 In between Pairs and Infinities of Agents
- B.18 Reward the Right Things -- Bibliography -- Index
- Part II. Preliminaries
- Part I. Introduction
- Appendix A. An Open Agenda for Complex Adaptive Social Systems
- Part III. Computational Modeling
- Index
- Figures
- -
- /
- Contents
- Part V. Conclusions
- Frontmatter --
- Tables
- Part IV. Models of Complex Adaptive Social Systems
- Preface
- Appendix B. Practices for Computational Modeling
- Bibliography