Offline RL

Learning Off-Policy with Online Planning CoRL 2021 Learning Routines for Effective Off-Policy Reinforcement Learning ICML 2021 Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare IJCAI 2021 Minimax Regret for Stochastic Shortest Path with Adversarial Costs and Known Transition COLT 2021 Mitigating Covariate Shift in Imitation Learning via Offline Data With Partial Coverage NeurIPS 2021 Model-Based Offline Planning ICLR 2021 Model-Free and Model-Based Policy Evaluation when Causality is Uncertain ICML 2021 Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs NeurIPS 2021 Nearly Horizon-Free Offline Reinforcement Learning NeurIPS 2021 Near-Optimal Offline Reinforcement Learning via Double Variance Reduction NeurIPS 2021 Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning AISTATS 2021 Near Optimal Reward-Free Reinforcement Learning ICML 2021 Non-asymptotic Confidence Intervals of Off-policy Evaluation: Primal and Dual Bounds ICLR 2021 Non-Stationary Off-Policy Optimization AISTATS 2021 No-regret learning with high-probability in adversarial Markov decision processes UAI 2021 Offline Constrained Multi-Objective Reinforcement Learning via Pessimistic Dual Value Iteration NeurIPS 2021 Offline Contextual Bandits with Overparameterized Models ICML 2021 Offline Meta Reinforcement Learning -- Identifiability Challenges and Effective Data Collection Strategies NeurIPS 2021 Offline Meta-Reinforcement Learning with Advantage Weighting ICML 2021 Offline Model-based Adaptable Policy Learning NeurIPS 2021 Offline Reinforcement Learning as One Big Sequence Modeling Problem NeurIPS 2021 Offline Reinforcement Learning from Human Feedback in Real-World Sequence-to-Sequence Tasks ACL 2021 Offline Reinforcement Learning from Images with Latent Space Models L4DC 2021 Offline Reinforcement Learning with Fisher Divergence Critic Regularization ICML 2021 Offline Reinforcement Learning with Pseudometric Learning ICML 2021