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The Sample Complexity of Policy Learning with Mu-Resets

arXiv cs.LG ↗ · 2026-08-11 缓存

This paper studies the sample complexity of policy learning under the mu-resets interaction protocol in reinforcement learning, resolving a question about the role of policy realizability and showing horizon dependence is exponential under all-policy concentrability and sqrt-exponential under pushforward concentrability.

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