Methods

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 A Contraction Approach to Model-based Reinforcement Learning AISTATS 2021 Acting in Delayed Environments with Non-Stationary Markov Policies ICLR 2021 Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills ICML 2021 Action Candidate Based Clipped Double Q-learning for Discrete and Continuous Action Tasks AAAI 2021 Action redundancy in reinforcement learning UAI 2021 Active Offline Policy Selection NeurIPS 2021 Adaptable Agent Populations via a Generative Model of Policies NeurIPS 2021 Adapting to misspecification in contextual bandits with offline regression oracles ICML 2021 Adapting to Reward Progressivity via Spectral Reinforcement Learning ICLR 2021 Adaptive Approximate Policy Iteration AISTATS 2021 Adaptive Ensemble Q-learning: Minimizing Estimation Bias via Error Feedback NeurIPS 2021 Adaptive Focus for Efficient Video Recognition ICCV 2021 Adaptive Information Seeking for Open-Domain Question Answering EMNLP 2021 Adaptive Online Packing-guided Search for POMDPs NeurIPS 2021 Adaptive Prior-Dependent Correction Enhanced Reinforcement Learning for Natural Language Generation AAAI 2021 Adaptive Procedural Task Generation for Hard-Exploration Problems ICLR 2021 Adaptive Reward-Free Exploration ALT 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 A Deep Reinforcement Learning Approach to First-Order Logic Theorem Proving AAAI 2021