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Sagan

Paper

On the Sample Complexity of Discounted Reinforcement Learning with Optimized Certainty Equivalents

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AI summary

arXiv:2605. 21763v1 Announce Type: cross Abstract: We study risk-sensitive reinforcement learning in finite discounted MDPs, where a generative model of the MDP is assumed to be available.