Network Models for Game Theory and Economics - 2004

Explore graph-theoretic and network models for large-population game theory and economics in this comprehensive lecture by Michael Kearns from the University of Pennsylvania. Delve into how players and organizations are represented as vertices in a graph, with payoffs and transactions constrained by the graph's topology. Examine how these models allow for detailed specification of social, technological, organizational, political, and regulatory structures in strategic and economic systems. Learn about algorithms for computing Nash, correlated, and Arrow-Debreu equilibria. Discover connections to related topics such as Bayesian and Markov networks for probabilistic modeling and inference. Gain insights into recent work combining these concepts with social network theory. This 1-hour 22-minute talk, presented at the Center for Language & Speech Processing (CLSP) at Johns Hopkins University in 2004, provides a thorough overview of network models and their applications in game theory and economics.