Stochastic Learning Dynamics and Speed of Convergence in Population Games

• 成果类型: Article
• 署名作者: Arieli, Itai; Young, H. Peyton
• 署名单位: Technion Israel Institute of Technology; University of Oxford
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA10740
• 发表日期: 2016
• 页码: 627-676
• 关键词: WEAKLY ACYCLIC GAMES; Nash equilibrium; uncoupled dynamics; RESPONSE DYNAMICS; EVOLUTION; selection

摘要

We study how long it takes for large populations of interacting agents to come close to Nash equilibrium when they adapt their behavior using a stochastic better reply dynamic. Prior work considers this question mainly for 2 x 2 games and potential games; here we characterize convergence times for general weakly acyclic games, including coordination games, dominance solvable games, games with strategic complementarities, potential games, and many others with applications in economics, biology, and distributed control. If players' better replies are governed by idiosyncratic shocks, the convergence time can grow exponentially in the population size; moreover, this is true even in games with very simple payoff structures. However, if their responses are sufficiently correlated due to aggregate shocks, the convergence time is greatly accelerated; in fact, it is bounded for all sufficiently large populations. We provide explicit bounds on the speed of convergence as a function of key structural parameters including the number of strategies, the length of the better reply paths, the extent to which players can influence the payoffs of others, and the desired degree of approximation to Nash equilibrium.