Simple approximate equilibria in large games

Abstract

We prove that in every normal form n-player game with m actions for each player, there exists an approximate Nash equilibrium in which each player randomizes uniformly among a set of O(log m + log n) pure actions. This result induces an O(N log log N)-time algorithm for computing an approximate Nash equilibrium in games where the number of actions is polynomial in the number of players (m=poly(n)); here N=nmn is the size of the game (the input size). Furthermore, when the number of actions is a fixed constant (m=O(1)) the same algorithm runs in O(Nlog log log N) time. In addition, we establish an inverse connection between the entropy of Nash equilibria in the game, and the time it takes to find such an approximate Nash equilibrium using the random sampling method.

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