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arXiv Machine Learning By Dominik Wagner, Leon Witzman, Luke Ong

Near-Optimal Reinforcement Learning for Constrained Recurrence Objectives

Read the original on arXiv Machine Learning →

arXiv:2511. 19849v2 Announce Type: replace-cross Abstract: Recurrence objectives, where a target region must be visited infinitely often, are a fundamental class of specifications for Markov decision processes (MDPs) and form the core of $\omega$-regular and linear temporal logic (LTL) objectives.

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