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Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

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Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives, , , and . (2018)cite arxiv:1810.04152.Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives., , , and . ICLR (Poster), OpenReview.net, (2019)Guided evolutionary strategies: augmenting random search with surrogate gradients., , , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 4264-4273. PMLR, (2019)Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research., , , , , , , , , and 12 other author(s). CoRR, (2023)Offline Policy Selection under Uncertainty., , , , and . CoRR, (2020)Conservative Q-Learning for Offline Reinforcement Learning., , , and . NeurIPS, (2020)Energy-Inspired Models: Learning with Sampler-Induced Distributions., , , and . NeurIPS, page 8499-8511. (2019)Oracle Inequalities for Model Selection in Offline Reinforcement Learning., , , , and . NeurIPS, (2022)Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion., , , , and . NeurIPS, page 8234-8244. (2018)Coupled Gradient Estimators for Discrete Latent Variables., , and . NeurIPS, page 24498-24508. (2021)