Reinforcement Learning

Inverse Decision Modeling: Learning Interpretable Representations of Behavior ICML 2021 Inverse Reinforcement Learning From Like-Minded Teachers AAAI 2021 Inverse Reinforcement Learning in a Continuous State Space with Formal Guarantees NeurIPS 2021 Inverse Reinforcement Learning with Explicit Policy Estimates AAAI 2021 Inverse Reinforcement Learning with Natural Language Goals AAAI 2021 Investigating vulnerabilities of deep neural policies UAI 2021 IQ-Learn: Inverse soft-Q Learning for Imitation NeurIPS 2021 Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies NeurIPS 2021 Is Pessimism Provably Efficient for Offline RL? ICML 2021 Is Reinforcement Learning More Difficult Than Bandits? A Near-optimal Algorithm Escaping the Curse of Horizon COLT 2021 Iterative Amortized Policy Optimization NeurIPS 2021 Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods AAAI 2021 Iterative Empirical Game Solving via Single Policy Best Response ICLR 2021 Iterative Shrinking for Referring Expression Grounding Using Deep Reinforcement Learning CVPR 2021 Kernel-Based Reinforcement Learning: A Finite-Time Analysis ICML 2021 Keyframe-Focused Visual Imitation Learning ICML 2021 Keyphrase Generation with Fine-Grained Evaluation-Guided Reinforcement Learning EMNLP 2021 Known unknowns: Learning novel concepts using reasoning-by-elimination UAI 2021 Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning NeurIPS 2021 Langevin Dynamics for Adaptive Inverse Reinforcement Learning of Stochastic Gradient Algorithms JMLR 2021 Language Conditioned Imitation Learning Over Unstructured Data RSS 2021 Language Model Augmented Relevance Score ACL 2021 Language Models are Few-Shot Butlers EMNLP 2021 Language Representations for Generalization in Reinforcement Learning ACML 2021 Large Batch Simulation for Deep Reinforcement Learning ICLR 2021