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cs.LG2024
Model-Free Robust Reinforcement Learning with Sample Complexity Analysis
Yudan Wang, Shaofeng Zou, Yue Wang
Distributionally Robust Reinforcement Learning (DR-RL) aims to derive a policy optimizing the worst-case performance within a predefined uncertainty set. Despite extensive research…
cs.LG2024
Constrained Reinforcement Learning Under Model Mismatch
Zhongchang Sun, Sihong He, Fei Miao +1
Existing studies on constrained reinforcement learning (RL) may obtain a well-performing policy in the training environment. However, when deployed in a real environment, it may ea…