Corruption-Robust Offline Two-Player Zero-Sum Markov Games

arXiv:2403.07933v1 Announce Type: cross
Abstract: We study data corruption robustness in offline two-player zero-sum Markov games. Given a dataset of realized trajectories of two players, an adversary is allowed to modify an $\epsilon$-fraction of it. The learner's goal is to identify an approximate Nash Equilibrium policy pair from the corrupted data. We consider this problem in linear Markov games under different degrees of data coverage and corruption. We start by providing an information-theoretic lower bound on the suboptimality gap of …

abstract arxiv corrupted data corruption cs.gt cs.lg data dataset epsilon equilibrium games identify markov nash equilibrium offline policy robust robustness study type