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Apr, 2022
非马尔科夫决策过程中PAC强化学习的马尔科夫抽象
Markov Abstractions for PAC Reinforcement Learning in Non-Markov Decision Processes
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Alessandro Ronca, Gabriel Paludo Licks, Giuseppe De Giacomo
TL;DR
本文提出了一种结合自动机学习和经典强化学习的算法，用于学习非马尔可夫决策流程中的马尔科夫抽象，并且证明该算法具有PAC保证。
Abstract
Our work aims at developing
reinforcement learning
algorithms that do not rely on the Markov assumption. We consider the class of
non-markov decision processes
where histories can be abstracted into a finite set
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