Deep RL

Neural-progressive hedging: Enforcing constraints in reinforcement learning with stochastic programming UAI 2022 Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-efficiency of Posterior Sampling COLT 2022 Object-Category Aware Reinforcement Learning NeurIPS 2022 Offline Reinforcement Learning at Multiple Frequencies CoRL 2022 Off-Policy Fitted Q-Evaluation with Differentiable Function Approximators: Z-Estimation and Inference Theory ICML 2022 Off-Policy Reinforcement Learning with Delayed Rewards ICML 2022 Online Ad Hoc Teamwork under Partial Observability ICLR 2022 Online Apprenticeship Learning AAAI 2022 Online Decision Transformer ICML 2022 Online Learning for Unknown Partially Observable MDPs AISTATS 2022 On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning ICLR 2022 On-Policy Model Errors in Reinforcement Learning ICLR 2022 On the Convergence Rate of Off-Policy Policy Optimization Methods with Density-Ratio Correction AISTATS 2022 On the Effectiveness of Fine-tuning Versus Meta-reinforcement Learning NeurIPS 2022 On the (In)Tractability of Reinforcement Learning for LTL Objectives IJCAI 2022 On the Sample Complexity of Learning Infinite-horizon Discounted Linear Kernel MDPs ICML 2022 On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL NeurIPS 2022 Open-Ended Reinforcement Learning with Neural Reward Functions NeurIPS 2022 Operator Splitting Value Iteration NeurIPS 2022 Optimistic Initialization for Exploration in Continuous Control AAAI 2022 Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees NeurIPS 2022 Optimizing Sequential Experimental Design with Deep Reinforcement Learning ICML 2022 Optimizing Tensor Network Contraction Using Reinforcement Learning ICML 2022 Option Transfer and SMDP Abstraction with Successor Features IJCAI 2022 Orchestrated Value Mapping for Reinforcement Learning ICLR 2022