Offline RL

Private Reinforcement Learning with PAC and Regret Guarantees ICML 2020 Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation ICML 2020 Provably Efficient Neural GTD for Off-Policy Learning NeurIPS 2020 Provably Good Batch Off-Policy Reinforcement Learning Without Great Exploration NeurIPS 2020 Q* Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison UAI 2020 Representations for Stable Off-Policy Reinforcement Learning ICML 2020 Revisiting Fundamentals of Experience Replay ICML 2020 RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning NeurIPS 2020 Scaling data-driven robotics with reward sketching and batch reinforcement learning RSS 2020 Self-Imitation Learning via Generalized Lower Bound Q-learning NeurIPS 2020 Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling ICML 2020 Variance-Reduced Off-Policy TDC Learning: Non-Asymptotic Convergence Analysis NeurIPS 2020 Batch Policy Learning under Constraints ICML 2019 CAB: Continuous Adaptive Blending for Policy Evaluation and Learning ICML 2019 Combining parametric and nonparametric models for off-policy evaluation ICML 2019 Divergence-Augmented Policy Optimization NeurIPS 2019 DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections NeurIPS 2019 Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables ICML 2019 Generalized Off-Policy Actor-Critic NeurIPS 2019 Imitation-Regularized Offline Learning AISTATS 2019 Importance Resampling for Off-policy Prediction NeurIPS 2019 Importance Sampling Policy Evaluation with an Estimated Behavior Policy ICML 2019 Interactive Reinforcement Learning with Dynamic Reuse of Prior Knowledge from Human and Agent Demonstrations IJCAI 2019 Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning NeurIPS 2019 More Efficient Off-Policy Evaluation through Regularized Targeted Learning ICML 2019