arXiv Machine Learning June 16, 2026 By Jongmin Lee, Ernest K. Ryu, Vaneet Aggarwal

Learning Policy from a Single Trajectory in Average-Reward Markov Decision Process

Read the original on arXiv Machine Learning →

arXiv:2606. 16729v1 Announce Type: new Abstract: While there is an extensive body of work characterizing the sample complexity of discounted cumulative-reward MDPs, finite sample analyses for average-reward MDPs have been limited, and most existing works rely on restrictive assumptions such as ergodicity or access to a generative model.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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