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BK

Cambridge (MA) ; London : The MIT Press, [2015]

xxii, 482 stran : barevné ilustrace ; 23 cm

ISBN 978-0-262-73189-8 (brožováno)

Obsahuje bibliografii na stranách 447-458 a rejstřík

001473643

0 Why Agent-Based Modeling? 1 // A Thought Experiment 3 Complex Systems and Emergence 5 Understanding Complex Systems and Emergence 7 Example 1: Integrative Understanding 7 Example 2: Differential Understanding 8 Agent-Based Modeling as Representational Infrastructure for Restructurations 13 Example: Predator-Prey Interactions 15 Example: Forest Fires 18 // 1 What Is Agent-Based Modeling? 21 // Ants 21 // Creating the Ant Foraging Model 22 Results and Observations from the Ant Model 27 What Good Is an Ant Model? 28 What Is Agent-Based Modeling? 32 // Agent-Based Models vs. Other Modeling Forms 32 Randomness vs. Determinism 34 When Is ABM Most Beneficial? 35 Trade-offs of ABM 36 What Is Needed to Understand ABM? 38 Conclusion 39 Explorations 40 // Beginner NetLogo Explorations 40 Ants and Other Model Explorations 41 Concept Explorations 41 NetLogo Explorations 42 // 2 Creating Simple Agent-Based Models 45 // Life 45 // Heroes and Cowards 68 Simple Economy 87 Summary 96 Explorations 97 // Chapter Model Explorations 97 NetLogo Explorations 99 // 3 Exploring and Extending Agent-Based Models 101 // The Fire Model 103 // Description of the Fire Model 104 First Extension: Probabilistic Transitions 110 Second Extension: Adding Wind 112 Third Extension: Allow Long-Distance Transmission 115 Summary of the Fire Model 116 Advanced Modeling Applications 117 The Diffusion-Limited Aggregation (DLA) Model 118 Description of Diffusion-Limited Aggregation 119 First Extension: Probabilistic Sticking

121 Second Extension: Neighbor Influence 122 Third Extension: Different Aggregates 125 Summary of the DLA Model 127 Advanced Modeling Applications 127 The Segregation Model 128 // Description of the Segregation Model 131 First Extension: Adding Multiple Ethnicities 134 Second Extension: Allowing Diverse Thresholds 136 Third Extension: Adding Diversity-Seeking Individuals 137 Summary of the Segregation Model 140 Advanced Urban Modeling Applications 140 The El Farol Model 141 // Description of the El Farol Model 141 // First Extension: Color Agents That Are More Successful Predictors 143 Second Extension: Average, Min, and Max Rewards 145 Third Extension: Histogram Reward Values 146 Summary of the El Farol Model 149 Advanced Modeling Applications 150 Conclusion 152 Explorations 152 // 4 Creating Agent-Based Models 157 // Designing Your Model 158 Choosing Your Questions 161 A Concrete Example 163 Choosing Your Agents 164 Choosing Agent Properties 165 Choosing Agent Behavior 166 Choosing Parameters of the Model 168 Summary of the Wolf Sheep Simple Model Design 169 Examining a Model 189 Multiple Runs 191 // Predator-Prey Models: Additional Context 193 Advanced Modeling Applications 195 Conclusion 196 Explorations 197 // 5 The Components of Agent-Based Modeling 203 // Overview 203 Agents 205 Properties 205 Behaviors (Actions) 209 Collections of Agents 211 The Granularity of an Agent 222 Agent Cognition 224 Other Kinds of Agents 232 Environments 234 // Spatial Environments 235 Network-Based

Environments 241 Special Environments 247 Interactions 257 Observer/User Interface 262 Schedule 268 Wrapping It All Up 271 Summary 275 Explorations 276 // 6 Analyzing Agent-Based Models 283 // Types of Measurements 283 Modeling the Spread of Disease 283 // Statistical Analysis of ABM: Moving beyond Raw Data 287 // The Necessity of Multiple Runs within ABM 288 Using Graphs to Examine Results in ABM 291 Analyzing Networks within ABM 296 Environmental Data and ABM 301 Summarizing Analysis of ABMs 305 Explorations 307 // 7 Verification, Validation, and Replication 311 // Correctness of a Model 311 Verification 312 Communication 313 Describing Conceptual Models 314 Verification Testing 315 Beyond Verification 317 Sensitivity Analysis and Robustness 321 Verification Benefits and Issues 324 Validation 325 // Macrovalidation vs. Micro validation 329 Face Validation vs. Empirical Validation 331 Validation Benefits and Questions 335 Replication 336 // Replication of Computational Models: Dimensions and Standards 337 Benefits of Replication 340 Recommendations for Model Replicators 341 Recommendations for Model Authors 344 Summary 346 Explorations 347 // 8 Advanced Topics and Applications 351 // Advanced Topics in ABM 351 Model Design Guidelines 353 Rule Extraction 356 // Using ABM for Communication, Persuasion, and Education 369 Human, Embedded, and Virtual Agents through Mediation 372 Hybrid Computational Methods 383 Some Advanced Computational Methods in NetLogo 391 Extensions to ABM

401 // Integration of Advanced Data Sources and Output 402 Speed 418 // Applications of ABM 419 // Revisiting the Trade-offs of ABM 423 The Future of ABM 424 Explorations 425 // Appendix: The Computational Roots of Agent-Based Modeling 431 // The Vignettes 433 // Cellular Automata and Agent-Based Modeling 433 // Genetic Algorithms, John Holland, and Complex Adaptive Systems 435 // Seymour Paperi, Logo, and the Turtle 439 // Object-Oriented Programming and the Actor Model 440 // Data Parallelism 442 // Computer Graphics, Particle Systems, and Boids 443 Conclusion 445 // References 447 Software and Models 459 Index 463