Stochastic learning dynamics and speed of convergence in population games

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 × 2 games and potential games; here we characterize convergence times for g...

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Main Authors: Arieli, I, Young, H
Format: Journal article
Published: Econometric Society 2016
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author Arieli, I
Young, H
author_facet Arieli, I
Young, H
author_sort Arieli, I
collection OXFORD
description 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 × 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.
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spelling oxford-uuid:407b0e16-824b-4b7e-b7cb-567cc7285e512022-03-26T14:38:10ZStochastic learning dynamics and speed of convergence in population gamesJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:407b0e16-824b-4b7e-b7cb-567cc7285e51Symplectic Elements at OxfordEconometric Society2016Arieli, IYoung, HWe 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 × 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.
spellingShingle Arieli, I
Young, H
Stochastic learning dynamics and speed of convergence in population games
title Stochastic learning dynamics and speed of convergence in population games
title_full Stochastic learning dynamics and speed of convergence in population games
title_fullStr Stochastic learning dynamics and speed of convergence in population games
title_full_unstemmed Stochastic learning dynamics and speed of convergence in population games
title_short Stochastic learning dynamics and speed of convergence in population games
title_sort stochastic learning dynamics and speed of convergence in population games
work_keys_str_mv AT arielii stochasticlearningdynamicsandspeedofconvergenceinpopulationgames
AT youngh stochasticlearningdynamicsandspeedofconvergenceinpopulationgames