Small-Support Approximate Correlated Equilibria

TL;DR

This paper proves the existence of small-support approximate correlated and coarse correlated equilibria in games, explores their computational aspects, and establishes NP-hardness for finding minimal support exact correlated equilibria.

Contribution

It introduces probabilistic methods to show small-support approximate equilibria exist and analyzes the computational complexity of finding such equilibria.

Findings

Existence of polylogarithmic support approximate correlated equilibria

Efficient random sampling for approximate coarse correlated equilibria

NP-hardness of finding minimal support exact correlated equilibria

Abstract

We prove the existence of approximate correlated equilibrium of support size polylogarithmic in the number of players and the number of actions per player. In particular, using the probabilistic method, we show that there exists a multiset of polylogarithmic size such that the uniform distribution over this multiset forms an approximate correlated equilibrium. Along similar lines, we establish the existence of approximate coarse correlated equilibrium with logarithmic support. We complement these results by considering the computational complexity of determining small-support approximate equilibria. We show that random sampling can be used to efficiently determine an approximate coarse correlated equilibrium with logarithmic support. But, such a tight result does not hold for correlated equilibrium, i.e., sampling might generate an approximate correlated equilibrium of support size \Omega(m) where m is the number of actions per player. Finally, we show that finding an exact correlated equilibrium with smallest possible support is NP-hard under Cook reductions, even in the case of two-player zero-sum games.