Oct 4, 2023 · This paper bridges the gap between robust statistics and statistical inference in reinforcement learning, offering a more versatile and reliable ...
Oct 4, 2023 · proposed algorithm for robust policy evaluation in reinforcement learning. Theoretical results on convergence rates, asymptotic normality ...
Jan 31, 2024 · Online Estimation and Inference for Robust Policy Evaluation in Reinforcement Learning. Distinguished Lecture / Joint Seminar Series.
In this article, we study the use of the online bootstrap method for inference in RL policy evaluation. In particular, we focus on the temporal difference (TD) ...
In this paper, we study the use of the online bootstrap method for statistical inference in RL. In particular, we focus on the temporal difference (TD) learning ...
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Jun 29, 2022 · (2018) proposed a statistical inference method for M-estimation problems based on fixed step-size SGD. Chen et al. (2020) derived two kinds of ...
Jul 18, 2023 · In this paper, we propose a robust policy evaluation algorithm in reinforcement learning, to feature outlier contamination and heavy-tailed ...
In a sequential decision-making problem, off-policy evaluation estimates the expected cumulative reward of a target policy using logged trajectory data ...
We study representation learning for Offline Reinforcement Learning (RL), focusing on the important task of Offline Policy Evaluation (OPE).
We study the problem of off-policy evaluation. (OPE) in reinforcement learning (RL), where the goal is to estimate the performance of a policy.