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cs.LG2024★ 2 cited
D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning
Rafael Rafailov, Kyle Hatch, Anikait Singh +9
Offline reinforcement learning algorithms hold the promise of enabling data-driven RL methods that do not require costly or dangerous real-world exploration and benefit from large…
cs.LG2021
Interpretable Local Tree Surrogate Policies
John Mern, Sidhart Krishnan, Anil Yildiz +2
High-dimensional policies, such as those represented by neural networks, cannot be reasonably interpreted by humans. This lack of interpretability reduces the trust users have in p…