Methods

A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation ICML 2021 Ad Headline Generation using Self-Critical Masked Language Model NAACL 2021 A DQN-based Approach to Finding Precise Evidences for Fact Verification ACL 2021 Adversarial Intrinsic Motivation for Reinforcement Learning NeurIPS 2021 Adversarially Guided Actor-Critic ICLR 2021 Adversarial Option-Aware Hierarchical Imitation Learning ICML 2021 Advice-Guided Reinforcement Learning in a non-Markovian Environment AAAI 2021 A General Offline Reinforcement Learning Framework for Interactive Recommendation AAAI 2021 Agent Modelling under Partial Observability for Deep Reinforcement Learning NeurIPS 2021 Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations NeurIPS 2021 A Heuristic Evaluation Function for Hand Strength Estimation in Gin Rummy AAAI 2021 A Hierarchical Reinforcement Learning Based Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems NeurIPS 2021 A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces AISTATS 2021 A Law of Iterated Logarithm for Multi-Agent Reinforcement Learning NeurIPS 2021 Algorithms for Fairness in Sequential Decision Making AISTATS 2021 Aligning an optical interferometer with beam divergence control and continuous action space CoRL 2021 Alohamora: Reviving HTTP/2 Push and Preload by Adapting Policies On the Fly NSDI 2021 A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning ICML 2021 A Max-Min Entropy Framework for Reinforcement Learning NeurIPS 2021 A Minimalist Approach to Offline Reinforcement Learning NeurIPS 2021 An Efficient Transfer Learning Framework for Multiagent Reinforcement Learning NeurIPS 2021 An Enhanced Advising Model in Teacher-Student Framework using State Categorization AAAI 2021 A New Formalism, Method and Open Issues for Zero-Shot Coordination ICML 2021 A New Representation of Successor Features for Transfer across Dissimilar Environments ICML 2021 A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning ICML 2021