markov decision process

Adaptive Approximate Policy Iteration AISTATS 2021 Adaptive Information Seeking for Open-Domain Question Answering EMNLP 2021 Adaptive Sampling for Best Policy Identification in Markov Decision Processes ICML 2021 Advice-Guided Reinforcement Learning in a non-Markovian Environment AAAI 2021 A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces AISTATS 2021 Algorithms for Fairness in Sequential Decision Making AISTATS 2021 A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning ICML 2021 An Exponential Lower Bound for Linearly Realizable MDP with Constant Suboptimality Gap NeurIPS 2021 A Nonmyopic Approach to Cost-Constrained Bayesian Optimization UAI 2021 A Provably Efficient Sample Collection Strategy for Reinforcement Learning NeurIPS 2021 Asymptotically Exact Error Characterization of Offline Policy Evaluation with Misspecified Linear Models NeurIPS 2021 A Universal 2-state n-action Adaptive Management Solver AAAI 2021 Average-Reward Learning and Planning with Options NeurIPS 2021 Building Decision Tree for Imbalanced Classification via Deep Reinforcement Learning ACML 2021 Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation COLT 2021 Communication efficient parallel reinforcement learning UAI 2021 Constrained Risk-Averse Markov Decision Processes AAAI 2021 Contingency-aware influence maximization: A reinforcement learning approach UAI 2021 Counterfactual Explanations in Sequential Decision Making Under Uncertainty NeurIPS 2021 DeepAveragers: Offline Reinforcement Learning By Solving Derived Non-Parametric MDPs ICLR 2021 Deep Reinforcement Learning for Multi-contact Motion Planning of Hexapod Robots IJCAI 2021 Distributionally Robust Imitation Learning NeurIPS 2021 Distributional Reinforcement Learning for Multi-Dimensional Reward Functions NeurIPS 2021 Efficient PAC Reinforcement Learning in Regular Decision Processes IJCAI 2021 Ensemble Bootstrapping for Q-Learning ICML 2021