Finite-time convergence and regret guarantees for neural reinforcement learning in POMDPs
Read the original at arxiv.org→arXiv:2611.07069v1 Announce Type: new Abstract: Reinforcement learning (RL) in Partially Observable Markov Decision Processes (POMDPs) is computationally challenging due to the curse of long-range dependence on...
Original headline: "Finite-Time Convergence and Regret Guarantees for Neural Reinforcement Learning in POMDPs"
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- Nov 6, 05:00 UTC arXiv cs.LG lead source Finite-Time Convergence and Regret Guarantees for Neural Reinforcement Learning in POMDPs