11 citations · 22 across the 5 of their papers we have counts for
4 papers · 1 filter
Model-Free Robust Average-Reward Reinforcement Learning
Yue Wang, Alvaro Velasquez, George Atia +2
Robust Markov decision processes (MDPs) address the challenge of model uncertainty by optimizing the worst-case performance over an uncertainty set of MDPs. In this paper, we focus…
Achieving the Asymptotically Optimal Sample Complexity of Offline Reinforcement Learning: A DRO-Based Approach
Yue Wang, Jinjun Xiong, Shaofeng Zou
Offline reinforcement learning aims to learn from pre-collected datasets without active exploration. This problem faces significant challenges, including limited data availability…
Robust Constrained Reinforcement Learning
Yue Wang, Fei Miao, Shaofeng Zou
Constrained reinforcement learning is to maximize the expected reward subject to constraints on utilities/costs. However, the training environment may not be the same as the test o…
Policy Gradient Method For Robust Reinforcement Learning
Yue Wang, Shaofeng Zou
This paper develops the first policy gradient method with global optimality guarantee and complexity analysis for robust reinforcement learning under model mismatch. Robust reinfor…