A comprehensive introduction to mathematical and agent-based modeling of social behavior
This 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 behavior
- Integrates cognitive science, social science, and cultural evolution
- Covers topics such as the philosophy of modeling, collective movement, segregation, contagion, polarization, the evolution of cooperation, the emergence of norms, networks, and the scientific process
- Discusses more advanced topics, including how to use models to build a more robust empirical research program
- An ideal introductory textbook for graduate students or advanced undergraduates
- An invaluable resource for practitioners
"Some of the most pressing questions of our time concern how groups behave, from political polarization and cooperation to collective action, social influence and cultural evolution. This book is intended to equip scholars in the social, behavioral, and cognitive sciences with a toolkit for thinking about and studying social dynamics using mathematical and computational models. Currently, there are two approaches for modeling social dynamics: mathematical models and agent-based models. In this book, Smaldino treats the two traditions as complementary, rather than separate. Combining theory-driven instruction on key mathematical and agent-based models of social dynamics and cultural evolution with practical, specific examples of how to use models, the book offers an introduction to both kinds of modelling and shows readers how to build their own models, analyze them, and integrate them with empirical research.The book assumes minimal background in either programming or advanced mathematics"--
