Contents Modeling of Socio-Economic Systems Agent-Based Modeling

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Transcription:

Contents 1 Modeling of Socio-Economic Systems... 1 1.1 Introduction... 1 1.2 Particular Difficulties of Modeling Socio-Economic Systems... 2 1.3 Modeling Approaches... 4 1.3.1 Qualitative Descriptions... 4 1.3.2 Detailed Models... 5 1.3.3 Simple Models... 6 1.3.4 Modeling Complex Systems... 9 1.4 Challenges of Socio-Economic Modeling... 11 1.4.1 Promises and Difficulties of the Experimental Approach... 12 1.4.2 Several Models Are Right... 13 1.4.3 No Known Model Is Right... 15 1.4.4 The Model Captures Some Features, But May Be Inadequate... 17 1.4.5 Different Interpretations of the Same Model... 19 1.5 Discussion and Outlook... 20 1.5.1 Pluralistic or Possibilistic Modeling and Multiple World Views: The Way Out?... 20 1.5.2 Where Social Scientists and Natural Scientists or Engineers Can Learn from Each Other... 21 References... 22 2 Agent-Based Modeling... 25 2.1 Why Develop and Use Agent-Based Models?... 26 2.1.1 Potential of Computer Simulation in the Socio-Economic Sciences... 26 2.1.2 Equation-Based Versus Agent-Based Approach... 27 2.1.3 Scientific Agent-Based Models Versus Computer Games... 28 2.1.4 Advantages of Agent-Based Simulations... 28 xi

xii Contents 2.1.5 Understanding Self-organization and Emergence... 29 2.1.6 Examples of Agent-Based Models... 33 2.1.7 Social Super-Computing... 34 2.2 Principles of Agent-Based Modeling... 35 2.2.1 Number of Parameters and Choice of Model... 37 2.3 Implementation and Computer Simulation of Agent-Based Models... 38 2.3.1 Coding Multi-agent Simulations and Available Software Packages... 38 2.3.2 Specification of Initial and Boundary Conditions, Interaction Network and Parameters... 39 2.3.3 Performing Multi-agent Simulations... 42 2.3.4 Presentation of Results... 46 2.3.5 Identification of the Minimum Model Ingredients... 50 2.3.6 Gaining an Analytical Understanding... 51 2.3.7 Some Problems and Limitations of Computational Modeling... 52 2.4 Practical Application of Agent-Based Models: Potentials and Limitations... 53 2.4.1 Stylized Facts and Prediction in Socio-Economic Systems... 53 2.4.2 Possibilities and Limitations in the Management of Socio-Economic Systems... 55 2.5 Summary, Discussion, and Outlook... 60 2.5.1 Future Prospects and Paradigm Shifts... 61 References... 63 3 Self-organization in Pedestrian Crowds... 71 3.1 Introduction... 71 3.2 Pedestrian Dynamics... 72 3.2.1 Short History of Pedestrian Modeling... 72 3.2.2 The Social Force Concept... 72 3.2.3 Specification of the Social Force Model... 74 3.2.4 Angular Dependence... 75 3.2.5 Evolutionary Calibration with Video Tracking Data... 76 3.3 Crowd Dynamics... 78 3.3.1 Analogies with Gases, Fluids, and Granular Media... 78 3.3.2 Self-organization of Pedestrian Crowds... 79 3.4 Evacuation Dynamics... 82 3.4.1 Evacuation and Panic Research... 82 3.4.2 Situations of Panic... 84 3.4.3 Force Model for Panicking Pedestrians... 85 3.4.4 Collective Phenomena in Situations of Panic... 85

Contents xiii 3.4.5 Some Warning Signs of Critical Crowd Conditions... 92 3.4.6 Evolutionary Optimization of Pedestrian Facilities... 93 3.5 Future Directions... 95 References... 96 4 Opinion Formation... 101 4.1 Introduction... 101 4.2 Model... 104 4.3 Results... 106 4.4 Discussion... 109 References... 112 5 Spatial Self-organization Through Success-Driven Mobility... 115 5.1 Introduction... 115 5.2 Discrete Model of Interactive Motion in Space... 117 5.3 Simulation Results... 119 5.3.1 Symmetric Interactions... 119 5.3.2 Asymmetric Interactions... 124 5.4 Conclusions... 126 References... 128 6 Cooperation in Social Dilemmas... 131 6.1 Introduction... 131 6.2 Stability Properties of Different Games... 132 6.3 Phase Transitions and Routes to Cooperation... 133 6.4 Relationship with Cooperation-Supporting Mechanisms... 134 6.5 Further Kinds of Transitions to Cooperation... 135 6.6 Summary... 137 References... 138 7 Co-evolution of Social Behavior and Spatial Organization... 139 7.1 Introduction... 139 7.2 Model... 140 7.3 Results... 142 7.4 Discussion... 149 References... 150 8 Evolution of Moral Behavior... 153 8.1 Introduction... 153 8.2 Results... 155 8.3 Discussion... 159 References... 165 9 Coordination and Competitive Innovation Spreading in Social Networks... 169 9.1 Introduction... 169 9.2 Model... 170

xiv Contents 9.3 Results... 172 9.4 Discussion... 176 References... 183 10 Heterogeneous Populations: Coexistence, Integration, or Conflict... 185 10.1 Introduction... 185 10.2 Model... 186 10.3 Results... 188 10.3.1 Evolution of Normative Behavior in the Stag Hunt Game... 188 10.3.2 Occurrence of Conflict in the Snowdrift Game... 191 10.4 Discussion... 193 References... 198 11 Social Experiments and Computing... 201 11.1 Introduction... 201 11.2 Experiment... 202 11.3 Discussion... 204 References... 208 12 Learning of Coordinated Behavior... 211 12.1 Introduction... 211 12.2 The Route Choice Game... 213 12.3 Classification of Symmetrical 2 2 Games... 216 12.4 Experimental Results... 218 12.4.1 Emergence of Cooperation and Punishment... 220 12.4.2 Preconditions for Cooperation... 224 12.4.3 Strategy Coefficients... 226 12.5 Multi-agent Simulation Model... 228 12.5.1 Simultaneous and Alternating Cooperation in the Prisoner s Dilemma... 231 12.6 Summary, Discussion, and Outlook... 233 References... 235 13 Response to Information... 239 13.1 Experimental Setup and Previous Results... 240 13.2 Is It Just an Unstable User Equilibrium?... 242 13.3 Explaining the Volatile Decision Dynamics... 246 13.4 Simulation of Reinforcement Learning and Emergence of Individual Response Patterns... 247 13.4.1 Potentials and Limitations of Decision Control... 251 13.4.2 Master Equation Description of Iterated Decisions... 256 13.5 Summary and Outlook... 257 References... 258

Contents xv 14 Systemic Risks in Society and Economics... 261 14.1 Introduction... 261 14.2 Socio-Economic Systems as Complex Systems... 262 14.2.1 Non-Linear Interactions and Power Laws... 263 14.2.2 Power Laws and Heavy-Tail Distributions... 264 14.2.3 Network Interactions and Systemic Risks Through Failure Cascades... 265 14.2.4 Self-Organized or Self-Induced Criticality... 267 14.2.5 Limits of Predictability, Randomness, Turbulence and Chaos... 268 14.2.6 The Illusion of Control... 269 14.2.7 The Logic of Failure... 271 14.3 The Example of Financial Market Instability... 271 14.4 Managing Complexity... 274 14.4.1 How to Profit from Complex Systems... 274 14.4.2 Reducing Network Vulnerability... 276 14.5 Summary, Discussion, and Outlook... 277 References... 279 15 Managing Complexity... 285 15.1 What Is Special About Complex Systems?... 285 15.1.1 Chaotic Dynamics and Butterfly Effect... 286 15.1.2 Self-organization, Competition, and Cooperation... 286 15.1.3 Phase Transitions and Catastrophe Theory... 288 15.1.4 Self-organized Criticality, Power Laws, and Cascading Effects... 288 15.2 Some Common Mistakes in the Management of Complex Systems... 290 15.2.1 The System Does Not Do What You Want It to Do... 290 15.2.2 Guided Self-organization Is Better Than Control... 291 15.2.3 Self-organized Networks and Hierarchies... 291 15.2.4 Faster Is Often Slower... 293 15.2.5 The Role of Fluctuations and Heterogeneity... 294 15.3 Summary and Outlook... 296 References... 297 16 Challenges in Economics... 301 16.1 Introduction... 301 16.2 Real-World Challenges... 302 16.3 Fundamental Challenges... 303 16.3.1 Homo Economicus... 304 16.3.2 The Efficient Market Hypothesis... 306 16.3.3 Equilibrium Paradigm... 307 16.3.4 Prevalence of Linear Models... 309 16.3.5 Representative Agent Approach... 310

xvi Contents 16.3.6 Lack of Micro-Macro Link and Ecological Systems Thinking... 313 16.3.7 Optimization of System Performance... 314 16.3.8 Control Approach... 316 16.3.9 Human Factors... 318 16.3.10 Information... 318 16.4 Role of Other Scientific Fields... 319 16.4.1 Econophysics, Ecology, Computer Science... 319 16.4.2 Social Sciences... 321 References... 323 Index... 331

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