arxiv
PublishedJune 1, 2026 at 4:00 AM
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PAC-Bayesian Reinforcement Learning Trains Generalizable Policies
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arXiv:2510.10544v3 Announce Type: replace-cross Abstract: We derive a novel PAC-Bayesian generalization bound for reinforcement learning that explicitly accounts for Markov dependencies in the data, through the chain's mixing time. This contributes to overcoming challenges in obtaining generalizatio
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Originally published on arxiv ↗