Policy Learning

Unsupervised Reinforcement Learning in Multiple Environments AAAI 2022 Unsupervised Skill Discovery via Recurrent Skill Training NeurIPS 2022 USHER: Unbiased Sampling for Hindsight Experience Replay CoRL 2022 Utility Theory for Sequential Decision Making ICML 2022 Value Function Approximations via Kernel Embeddings for No-Regret Reinforcement Learning ACML 2022 Value Function Decomposition for Iterative Design of Reinforcement Learning Agents NeurIPS 2022 Versatile Offline Imitation from Observations and Examples via Regularized State-Occupancy Matching ICML 2022 When Is Partially Observable Reinforcement Learning Not Scary? COLT 2022 When to Update Your Model: Constrained Model-based Reinforcement Learning NeurIPS 2022 Abstract Value Iteration for Hierarchical Reinforcement Learning AISTATS 2021 Accelerating Quadratic Optimization with Reinforcement Learning NeurIPS 2021 Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies ICML 2021 Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning NeurIPS 2021 A Collaborative Multi-agent Reinforcement Learning Framework for Dialog Action Decomposition EMNLP 2021 A Constrained Multi-Objective Reinforcement Learning Framework CoRL 2021 Acting in Delayed Environments with Non-Stationary Markov Policies ICLR 2021 Action redundancy in reinforcement learning UAI 2021 Adaptable Agent Populations via a Generative Model of Policies NeurIPS 2021 Adaptive Approximate Policy Iteration AISTATS 2021 Adaptive Information Seeking for Open-Domain Question Answering EMNLP 2021 Adaptive Risk Sensitive Model Predictive Control with Stochastic Search L4DC 2021 Adaptive Sampling for Best Policy Identification in Markov Decision Processes ICML 2021 Addressing Action Oscillations through Learning Policy Inertia AAAI 2021 A decentralized policy gradient approach to multi-task reinforcement learning UAI 2021 Adversarial Option-Aware Hierarchical Imitation Learning ICML 2021