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Variance-Aware Fine-Grained Gap-Dependent Bounds for Online Reinforcement Learning

arXiv:2610.04752v1 Announce Type: new Abstract: We study model-free online reinforcement learning (RL) for episodic tabular Markov decision processes, focusing on both gap-dependent regret and policy switching cost. While fine-grained gap-dependent analysis has been established for model-free RL al…

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  1. 2026-10-06 04:00 · arXiv stat.ML
    Variance-Aware Fine-Grained Gap-Dependent Bounds for Online Reinforcement Learning

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