Policy Learning

What Can Learned Intrinsic Rewards Capture? ICML 2020 Accelerating Imitation Learning with Predictive Models AISTATS 2019 A Composable Specification Language for Reinforcement Learning Tasks NeurIPS 2019 Action Robust Reinforcement Learning and Applications in Continuous Control ICML 2019 Active Exploration in Markov Decision Processes AISTATS 2019 Adaptive Auxiliary Task Weighting for Reinforcement Learning NeurIPS 2019 Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates NeurIPS 2019 A Divergence Minimization Perspective on Imitation Learning Methods CoRL 2019 Adversarial Imitation Learning from Incomplete Demonstrations IJCAI 2019 A Family of Robust Stochastic Operators for Reinforcement Learning NeurIPS 2019 A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation NeurIPS 2019 Almost Horizon-Free Structure-Aware Best Policy Identification with a Generative Model NeurIPS 2019 An Empirical Comparison on Imitation Learning and Reinforcement Learning for Paraphrase Generation EMNLP 2019 An Imitation Learning Approach to Unsupervised Parsing ACL 2019 An Improved Convergence Analysis of Stochastic Variance-Reduced Policy Gradient UAI 2019 An Investigation of Model-Free Planning ICML 2019 ARAML: A Stable Adversarial Training Framework for Text Generation EMNLP 2019 A Regularized Approach to Sparse Optimal Policy in Reinforcement Learning NeurIPS 2019 A Strongly Asymptotically Optimal Agent in General Environments IJCAI 2019 A Theory of Regularized Markov Decision Processes ICML 2019 A Tighter Analysis of Randomised Policy Iteration UAI 2019 Augmenting Markov Decision Processes with Advising AAAI 2019 Automatic Successive Reinforcement Learning with Multiple Auxiliary Rewards IJCAI 2019 Better Exploration with Optimistic Actor Critic NeurIPS 2019 Better, Faster, Stronger Sequence Tagging Constituent Parsers NAACL 2019