An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo (The MIT Press)

Description

A comprehensive and hands-on introduction to the core concepts, methods, and applications of agent-based modeling, including detailed NetLogo examples. The advent of widespread fast computing has enabled us to work on more complex problems and to build and analyze more complex models. This book provides an introduction to one of the primary methodologies for research in this new field of knowledge. Agent-based modeling (ABM) offers a new way of doing science: by conducting computer-based experiments. ABM is applicable to complex systems embedded in natural, social, and engineered contexts, across domains that range from engineering to ecology. An Introduction to Agent-Based Modeling offers a comprehensive description of the core concepts, methods, and applications of ABM. Its hands-on approach—with hundreds of examples and exercises using NetLogo—enables readers to begin constructing models immediately, regardless of experience or discipline. The book first describes the nature and rationale of agent-based modeling, then presents the methodology for designing and building ABMs, and finally discusses how to utilize ABMs to answer complex questions. Features in each chapter include step-by-step guides to developing models in the main text; text boxes with additional information and concepts; end-of-chapter explorations; and references and lists of relevant reading. There is also an accompanying website with all the models and code. front-cover front-page Copyright Page Contents Preface Who We Wrote This For NetLogo and the Textbook Learning Objectives Features Organization Chapters 0 and 1 and the Appendix: What are ABMS Chapters 2,3,4 and 5: How to build ABMS Chapters 6,7 and 8: How to analyze and build ABMs Acknowledgements 0 Why Agent-Based Modeling? A Thought Experiment Complex Systems and Emergence Understanding Complex Systems and Emergence Example 1: Integrative Understanding Example 2: Differential Understanding Agent-Based Modeling as Representational Infrastructure for Restructurations Example: Predator-Prey Interactions Example: Forest Fires 1 What Is Agent-Based Modeling? Ants Creating the Ant Foraging Model Results and Observations from the Ant Model What Good Is an Ant Model? What Is Agent-Based Modeling? Agent-Based Models vs. Other Modeling Forms Randomness vs. Determinism When Is ABM Most Beneficial? Trade-offs of ABM What Is Needed to Understand ABM? Conclusion Explorations Beginner NetLogo Explorations Ants and Other Model Explorations Concept Explorations NetLogo Explorations 2 Creating Simple Agent-Based Models Life Heroes and Cowards Simple Economy Summary Explorations Chapter Model Explorations NetLogo Explorations 3 Exploring and Extending Agent-Based Models The Fire Model Description of the Fire Model First Extension: Probabilistic Transitions Second Extension: Adding Wind Third Extension: Allow Long-Distance Transmission Summary of the Fire Model Advanced Modeling Applications The Diffusion-Limited Aggregation (DLA) Model Description of Diffusion-Limited Aggregation First Extension: Probabilistic Sticking Second Extension: Neighbor Influence Third Extension: Different Aggregates Summary of the DLA Model Advanced Modeling Applications The Segregation Model Description of the Segregation Model First Extension: Adding Multiple Ethnicities Second Extension: Allowing Diverse Thresholds Third Extension: Adding Diversity-Seeking Individuals Summary of the Segregation Model Advanced Urban Modeling Applications The El Farol Model Description of the El Farol Model First Extension: Color Agents That Are More Successful Predictors Second Extension: Average, Min, and Max Rewards Third Extension: Histogram Reward Values Summary of the El Farol Model Advanced Modeling Applications Conclusion Explorations 4 Creating Agent-Based Models Designing Your Model Choosing Your Questions A Concrete Example Choosing Your Agents Choosing Agent Properties Choosing Agent Behavior Choosing Parameters of the Model Summary of the Wolf Sheep Simple Model Design Examining a Model Multiple Runs Predator-Prey Models: Additional Context Advanced Modeling Applications Conclusion Explorations 5 The Components of Agent-Based Modeling Overview Agents Properties Behaviors (Actions) Collections of Agents The Granularity of an Agent Agent Cognition Other Kinds of Agents Environments Spatial Environments Network-Based Environments Special Environments Interactions Observer/User Interface Schedule Wrapping It All Up Summary Explorations 6 Analyzing Agent-Based Models Types of Measurements Modeling the Spread of Disease Statistical Analysis of ABM: Moving beyond Raw Data The Necessity of Multiple Runs within ABM Using Graphs to Examine Results in ABM Analyzing Networks within ABM Environmental Data and ABM Summarizing Analysis of ABMs Explorations 7 Verification, Validation, and Replication Correctness of a Model Verification Communication Describing Conceptual Models Verification Testing Beyond Verification Sensitivity Analysis and Robustness Verification Benefits and Issues Validation Macrovalidation vs. Microvalidation Face Validation vs. Empirical Validation Validation Benefits and Questions Replication Replication of Computational Models: Dimensions and Standards Benefits of Replication Recommendations for Model Replicators Recommendations for Model Authors Summary Explorations 8 Advanced Topics and Applications Advanced Topics in ABM Model Design Guidelines Rule Extraction Using ABM for Communication, Persuasion, and Education Human, Embedded, and Virtual Agents through Mediation Hybrid Computational Methods Some Advanced Computational Methods in NetLogo Extensions to ABM Integration of Advanced Data Sources and Output Speed Applications of ABM Revisiting the Trade-offs of ABM The Future of ABM Explorations Appendix: The Computational Roots of Agent-Based Modeling The Vignettes Cellular Automata and Agent-Based Modeling Genetic Algorithms, John Holland, and Complex Adaptive Systems Seymour Papert, Logo, and the Turtle Object-Oriented Programming and the Actor Model Data Parallelism Computer Graphics, Particle Systems, and Boids Conclusion References Software and Models Index