Modeling Social Behavior

Mathematical and Agent-Based Models of Social Dynamics and Cultural Evolution

Häftad, Engelska, 2023

545 kr

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Beskrivning

A comprehensive introduction to mathematical and agent-based modeling of social behaviorThis book provides a unified, theory-driven introduction to key mathematical and agent-based models of social dynamics and cultural evolution, teaching readers how to build their own models, analyze them, and integrate them with empirical research programs. It covers a variety of modeling topics, each exemplified by one or more archetypal models, and helps readers to develop strong theoretical foundations for understanding social behavior. Modeling Social Behavior equips social, behavioral, and cognitive scientists with an essential tool kit for thinking about and studying complex social systems using mathematical and computational models.Combines both mathematical and agent-based modeling of social behaviorIntegrates cognitive science, social science, and cultural evolutionCovers topics such as the philosophy of modeling, collective movement, segregation, contagion, polarization, the evolution of cooperation, the emergence of norms, networks, and the scientific processDiscusses more advanced topics, including how to use models to build a more robust empirical research programAn ideal introductory textbook for graduate students or advanced undergraduatesAn invaluable resource for practitioners

Produktinformation

Utgivningsdatum:2023-10-03
Mått:178 x 254 x 25 mm
Vikt:762 g
Format:Häftad
Språk:Engelska
Antal sidor:360
Förlag:Princeton University Press
ISBN:9780691224145

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Mer om författaren

Paul E. Smaldino is professor of cognitive and information sciences at the University of California, Merced, and external professor at the Santa Fe Institute.

Recensioner i media

"An important contribution to the field of social dynamics."---Adriana A. Maldonado-Chaparro, The Quarterly Review of Biology

Innehållsförteckning

PrefaceHow to Use This BookWhy This Book Uses NetLogo But You Don’t Have ToSummary of ChaptersAcknowledgments1 Doing Violence to Reality1.1 Flocking Birds and Boids1.2 What Are Models?1.3 The Parable of the Cubist Chicken1.4 Decomposition1.5 Formal Theory in the Inexact Sciences1.6 Why Model?1.7 Some Models of Note1.8 Equation-Based Models and Agent-Based Models1.9 Fine-Grained and Coarse-Grained Models1.10 The Journey Begins2 Particles2.1 NetLogo Basics2.2 Programming Basics2.3 Particle World2.4 Coding the Model2.5 The Components of a Model2.6 Describing a Model2.7 Flocking2.8 Reflections2.9 Going Deeper2.10 Exploration3 The Schelling Chapter3.1 The Puzzle of Segregation3.2 A Model of Segregation3.3 A Formal Description of the Model3.4 Thinking about Consequences3.5 Coding the Model3.6 The Power of Play3.7 Model Analysis3.8 Analyzing the Segregation Model3.9 Reflections3.10 Going Deeper3.11 Exploration4 Contagion4.1 The Diffusion of Innovations4.2 Spontaneous Adoption4.3 Social Influence: The SI Model4.4 The Analytical SI Model4.5 Getting Better: The SIS Model4.6 Staying Better: The SIR Model4.7 Reflections4.8 Going Deeper4.9 Exploration5 Opinion Dynamics5.1 Building a Model of Opinion Dynamics5.2 Opinion Dynamics Under Positive Influence5.3 Bounded Confidence5.4 Negative Influence5.5 Multiple Opinions, Polarization, and Extremism5.6 Reflections5.7 Going Deeper5.8 Exploration6 Cooperation6.1 The Prisoner’s Dilemma6.2 Evolutionary Dynamics6.3 Cooperation and Assortment6.4 Reducing Assortment6.5 Positive Assortment and Hamilton’s Rule6.6 Reciprocity6.7 The Evolutionary Stability of Reciprocity6.8 Reflections6.9 Going Deeper6.10 Exploration7 Coordination7.1 Norms with Symmetric Payoffs7.2 Group-Beneficial Norms7.3 Group-Beneficial Norms in a Structured Population7.4 Division of Labor7.5 Reflections7.6 Going Deeper7.7 Exploration8 The Scientific Process8.1 Science as Hypothesis Testing8.2 Bayes’ Theorem8.3 Science as Bayesian Inference8.4 Science as a Population Process8.5 Science as a Cultural Process8.6 Why the Most Newsworthy Science Might Be the Least Trustworthy8.7 Reflections8.8 Going Deeper8.9 Exploration9 Networks9.1 Network Building Blocks9.2 Network Architectures: Order and Chaos9.3 Small-World Networks: Short Paths and Strong Clustering9.4 Simple vs. Complex Contagion on Small-World Networks9.5 Preferential Attachment9.6 Other Social Drivers of Network Structure9.7 Reflections9.8 Going Deeper9.9 Exploration10 Models and Reality10.1 The Mapping Problem10.2 Nine Lessons for Turning an Idea into a Model10.3 Analyzing Your Model in Light of Itself10.4 Analyzing Your Model in Light of Empirical Data10.5 Fitting Models to Data on a Rugged Landscape10.6 Reflections11 Maps and Territories11.1 The Map Is Not The Territory11.2 We Need Many Maps11.3 The Journey ContinuesImage CreditsBibliographyIndex