Model Thinking: Essential Tools for Complex World

This module introduces the reasons for modeling and covers models of segregation and peer effects, including Schelling's segregation model and the standing ovation model.

This module explores aggregation concepts, including the Central Limit Theorem, Game of Life, cellular automata, and preference aggregation. It also covers decision-making models and probability basics.

This module covers different approaches to modeling human behavior, including rational actor, behavioral, and rule-based models. It also introduces categorical and linear models, including regression analysis.

This module explores tipping point models, including percolation and contagion models. It also covers economic growth models, including exponential growth and the Solow growth model.

This module examines the role of diversity in problem-solving and innovation, and introduces Markov processes and their applications in various fields.

This module consists of a midterm exam covering the content from modules 1-10.

This module covers Lyapunov functions and their applications in determining system outcomes. It also explores coordination games and the emergence of culture.

This module explores path dependence using urn models and relates it to increasing returns and tipping points. It also covers network structure, formation, and function.

This module discusses sources of randomness, random walk models, and their applications. It also introduces the Colonel Blotto game and its applications in competition modeling.

This module covers the Prisoners' Dilemma, collective action problems, and common pool resource issues. It also introduces mechanism design, including auctions and public project allocation.

This module covers replicator dynamics, Fisher's fundamental theorem, and their applications in learning and evolution. It also discusses prediction models and the concept of many-model thinking.

This module consists of a final exam covering the content from modules 12-21.