Regularization for Strategy Exploration in Empirical Game-Theoretic Analysis

Yongzhao Wang (University of Michigan), Michael P. Wellman (University of Michigan)

Abstract

We propose a novel meta-strategy solver called regularized replicator dynamics (RRD) for empirical game-theoretic analysis and show that RRD outperforms existing meta strategy solvers in various games.