An Approximate Dynamic Programming Approach to Repeated Games with Vector Losses

A seminal study showed repeated games with vector payoffs, which has had wide-ranging applications to decision making under uncertainty. Although this characterized the achievable guarantees in such long-run average payoff criterion, characterization and computation of these discounted criterion have remained a significant gap literature. In “An Approximate Dynamic Programming Approach Repeated Games Vector Losses,” V. Kamble, P. Loiseau, J. Walrand develop set-valued dynamic programming approach along an approximation framework fully address problem. This theory results new algorithms that beat state art for as exact regret minimization well-known problem prediction expert advice.