optimal policy

Improving the Knowledge Gradient Algorithm NeurIPS 2023 Keep-Alive Caching for the Hawkes process UAI 2023 Learning Optimal Policy for Simultaneous Machine Translation via Binary Search ACL 2023 Probabilistic Inference in Reinforcement Learning Done Right NeurIPS 2023 Sample Efficient Model-free Reinforcement Learning from LTL Specifications with Optimality Guarantees IJCAI 2023 The Unintended Consequences of Discount Regularization: Improving Regularization in Certainty Equivalence Reinforcement Learning ICML 2023 Utilizing Prior Solutions for Reward Shaping and Composition in Entropy-Regularized Reinforcement Learning AAAI 2023 Beyond No Regret: Instance-Dependent PAC Reinforcement Learning COLT 2022 Challenging Common Assumptions in Convex Reinforcement Learning NeurIPS 2022 DeepTOP: Deep Threshold-Optimal Policy for MDPs and RMABs NeurIPS 2022 Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees NeurIPS 2022 Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs ICLR 2022 On the (In)Tractability of Reinforcement Learning for LTL Objectives IJCAI 2022 Planning with Participation Constraints AAAI 2022 Recursive Reinforcement Learning NeurIPS 2022 Reinforcement Learning with Stochastic Reward Machines AAAI 2022 Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes ICML 2022 X-MEN: guaranteed XOR-maximum entropy constrained inverse reinforcement learning UAI 2022 A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning ICML 2021 A Universal 2-state n-action Adaptive Management Solver AAAI 2021 Automated Reasoning and Learning for Automated Payroll Management AAAI 2021 Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms NeurIPS 2021 Deciding What to Learn: A Rate-Distortion Approach ICML 2021 Dynamic Planning and Learning under Recovering Rewards ICML 2021 Efficient PAC Reinforcement Learning in Regular Decision Processes IJCAI 2021