Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting

NeurIPS 2017 Yue WangWei ChenYuting LiuZhi-Ming MaTie-Yan Liu

In reinforcement learning (RL) , one of the key components is policy evaluation, which aims to estimate the value function (i.e., expected long-term accumulated reward) of a policy. With a good policy evaluation method, the RL algorithms will estimate the value function more accurately and find a better policy... (read more)

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