Minimax Regret Bounds for Reinforcement Learning

Mohammad Gheshlaghi Azar, Ian Osband, Rémi Munos

Abstract: We consider the problem of provably optimal exploration in reinforcement learning for finite horizon MDPs. We show that an optimistic modification to value iteration achieves a regret bound of $\ti...