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20212026
most citedPolicy Gradient and Actor-Critic Learning in Continuous Time and Space: Theory and Algorithms

17 citations · 20 across the 16 of their papers we have counts for

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cs.LG2021★ 17 cited

Policy Gradient and Actor-Critic Learning in Continuous Time and Space: Theory and Algorithms

Yanwei Jia, Xun Yu Zhou

We study policy gradient (PG) for reinforcement learning in continuous time and space under the regularized exploratory formulation developed by Wang et al. (2020). We represent th…

cs.LG2021

Policy Evaluation and Temporal-Difference Learning in Continuous Time and Space: A Martingale Approach

Yanwei Jia, Xun Yu Zhou

We propose a unified framework to study policy evaluation (PE) and the associated temporal difference (TD) methods for reinforcement learning in continuous time and space. We show…