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News/Near Minimax Rate for Quantile Distributional Reinforcement Learning
arxiv
PublishedOctober 22, 2026 at 4:00 AM

Near Minimax Rate for Quantile Distributional Reinforcement Learning

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arXiv:2610.29595v1 Announce Type: cross Abstract: In this paper, we study quantile distributional policy evaluation, where the return distribution under a given policy is approximated by the quantile Bellman fixed point $\bm\eta_m$. We investigate the statistical accuracy of estimating $\bm\eta_m$ a

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