arXiv Machine Learning July 14, 2026 By Miao Lu, Han Zhong, Tong Zhang, Jose Blanchet

Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms

Read the original on arXiv Machine Learning →

arXiv:2404. 03578v3 Announce Type: replace Abstract: The sim-to-real gap, which represents the disparity between training and testing environments, poses a significant challenge in reinforcement learning (RL).

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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