Methods

Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback NeurIPS 2022 Near-Optimal Reward-Free Exploration for Linear Mixture MDPs with Plug-in Solver ICLR 2022 Near-Optimal Sample Complexity Bounds for Constrained MDPs NeurIPS 2022 Neighborhood Mixup Experience Replay: Local Convex Interpolation for Improved Sample Efficiency in Continuous Control Tasks L4DC 2022 NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning NeurIPS 2022 Neural-progressive hedging: Enforcing constraints in reinforcement learning with stochastic programming UAI 2022 Non-Linear Coordination Graphs NeurIPS 2022 Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-efficiency of Posterior Sampling COLT 2022 Non-Markovian Reward Modelling from Trajectory Labels via Interpretable Multiple Instance Learning NeurIPS 2022 OAM: An Option-Action Reinforcement Learning Framework for Universal Multi-Intersection Control AAAI 2022 Object-Category Aware Reinforcement Learning NeurIPS 2022 Offline Goal-Conditioned Reinforcement Learning via f-Advantage Regression NeurIPS 2022 Offline Meta-Reinforcement Learning with Online Self-Supervision ICML 2022 Offline Multi-Agent Reinforcement Learning with Knowledge Distillation NeurIPS 2022 Offline policy optimization with eligible actions UAI 2022 Offline Policy Selection under Uncertainty AISTATS 2022 Offline Reinforcement Learning as Anti-exploration AAAI 2022 Offline Reinforcement Learning at Multiple Frequencies CoRL 2022 Offline Reinforcement Learning for Visual Navigation CoRL 2022 Offline Reinforcement Learning: Fundamental Barriers for Value Function Approximation COLT 2022 Offline reinforcement learning under value and density-ratio realizability: The power of gaps UAI 2022 Offline Reinforcement Learning with Implicit Q-Learning ICLR 2022 Offline Reinforcement Learning with Realizability and Single-policy Concentrability COLT 2022 Offline Reinforcement Learning with Value-based Episodic Memory ICLR 2022 Offline RL Policies Should Be Trained to be Adaptive ICML 2022