May 27, 2024, 4:45 a.m. | Reda Ouhamma, Maryam Kamgarpour

cs.LG updates on arXiv.org arxiv.org

arXiv:2312.08008v2 Announce Type: replace-cross
Abstract: We consider decentralized learning for zero-sum games, where players only see their payoff information and are agnostic to actions and payoffs of the opponent. Previous works demonstrated convergence to a Nash equilibrium in this setting using double time-scale algorithms under strong reachability assumptions. We address the open problem of achieving an approximate Nash equilibrium efficiently with an uncoupled and single time-scale algorithm under weaker conditions. Our contribution is a rational and convergent algorithm, utilizing Tsallis-entropy …

abstract algorithm algorithms arxiv convergence cs.gt cs.lg decentralized equilibria equilibrium games information markov nash equilibrium replace scale sum type

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