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  • 论文公开站arXiv

    Hitting-Time Bounds for Asynchronous Q-Learning

    We study the last iterate of standard asynchronous Q-learning from a single trajectory of a finite Markov decision process. The trajectory follows a fixed behavior policy whose state--action chain is irreducible and may be periodic. For discount factor $γ$, write $H=(1-γ)^{-1}$,