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Offline RL

725 directly classified papers

Papers per year

Papers

Target-Based Temporal-Difference Learning ICML 2019
Batch Policy Learning under Constraints ICML 2019
Trajectory-Based Off-Policy Deep Reinforcement Learning ICML 2019
Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning NIPS 2019
Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction NIPS 2019
Safe Policy Improvement with Baseline Bootstrapping ICML 2019
Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift AAAI 2019
Importance Sampling Policy Evaluation with an Estimated Behavior Policy ICML 2019
Combining parametric and nonparametric models for off-policy evaluation ICML 2019
Off-Policy Deep Reinforcement Learning without Exploration ICML 2019
More Efficient Off-Policy Evaluation through Regularized Targeted Learning ICML 2019
Interactive Reinforcement Learning with Dynamic Reuse of Prior Knowledge from Human and Agent Demonstrations IJCAI 2019
Imitation-Regularized Offline Learning AISTATS 2019
Policy Poisoning in Batch Reinforcement Learning and Control NIPS 2019
Online Stochastic Shortest Path with Bandit Feedback and Unknown Transition Function NIPS 2019
Surrogate Objectives for Batch Policy Optimization in One-step Decision Making NIPS 2019
Unobserved Is Not Equal to Non-existent: Using Gaussian Processes to Infer Immediate Rewards Across Contexts IJCAI 2019
CAB: Continuous Adaptive Blending for Policy Evaluation and Learning ICML 2019
Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables ICML 2019
Optimistic Policy Optimization via Multiple Importance Sampling ICML 2019
Self-Imitation Learning ICML 2018
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor ICML 2018
More Robust Doubly Robust Off-policy Evaluation ICML 2018
Representation Balancing MDPs for Off-policy Policy Evaluation NIPS 2018
Exponentially Weighted Imitation Learning for Batched Historical Data NIPS 2018