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News/Efficient Q-Learning and Actor-Critic Methods for Robust Average-Reward Reinforcement Learning
arxiv
PublishedJuly 14, 2026 at 4:00 AM

Efficient Q-Learning and Actor-Critic Methods for Robust Average-Reward Reinforcement Learning

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arXiv:2506.07040v4 Announce Type: replace-cross Abstract: We study model-free methods for distributionally robust infinite-horizon average-reward Markov decision processes (MDPs). We present non-asymptotic convergence analyses of Q-learning and actor-critic algorithms for robust average-reward MDPs

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