Best-Response Dynamics, Playing Sequences, and Convergence to Equilibrium in Random Games
33 Pages Posted: 18 Feb 2021 Last revised: 18 Nov 2022
Date Written: January 11, 2021
Abstract
We analyze the performance of the best-response dynamic across all normal-form games using a random games approach. The playing sequence---the order in which players update their actions---is essentially irrelevant in determining whether the dynamic converges to a Nash equilibrium in certain classes of games (e.g. in potential games) but, when evaluated across all possible games, convergence to equilibrium depends on the playing sequence in an extreme way. Our main asymptotic result shows that the best-response dynamic converges to a pure Nash equilibrium in a vanishingly small fraction of all (large) games when players take turns according to a fixed cyclic order. By contrast, when the playing sequence is random, the dynamic converges to a pure Nash equilibrium if one exists in almost all (large) games.
Keywords: Best-response dynamics, equilibrium convergence, random games, learning models in games
JEL Classification: C62, C72, C73, D83
Suggested Citation: Suggested Citation