Reinforcement Learning

Optimally Solving Two-Agent Decentralized POMDPs Under One-Sided Information Sharing ICML 2020 Optimistic Policy Optimization with Bandit Feedback ICML 2020 Optimistic robust linear quadratic dual control L4DC 2020 Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement Learning AISTATS 2020 Optimizing for the Future in Non-Stationary MDPs ICML 2020 Optimizing the Factual Correctness of a Summary: A Study of Summarizing Radiology Reports ACL 2020 Option Discovery in the Absence of Rewards with Manifold Analysis ICML 2020 OPtions as REsponses: Grounding behavioural hierarchies in multi-agent reinforcement learning ICML 2020 Options of Interest: Temporal Abstraction with Interest Functions AAAI 2020 “Other-Play” for Zero-Shot Coordination ICML 2020 PackIt: A Virtual Environment for Geometric Planning ICML 2020 PADS: Policy-Adapted Sampling for Visual Similarity Learning CVPR 2020 Parameterized Indexed Value Function for Efficient Exploration in Reinforcement Learning AAAI 2020 Partially Observable Markov Decision Process Modelling for Assessing Hierarchies ACML 2020 Partner Selection for the Emergence of Cooperation in Multi-Agent Systems Using Reinforcement Learning AAAI 2020 Path Planning Problems with Side Observations—When Colonels Play Hide-and-Seek AAAI 2020 PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning NeurIPS 2020 Periodic Q-Learning L4DC 2020 Pessimism About Unknown Unknowns Inspires Conservatism COLT 2020 PFRL: Pose-Free Reinforcement Learning for 6D Pose Estimation CVPR 2020 Pipeline PSRO: A Scalable Approach for Finding Approximate Nash Equilibria in Large Games NeurIPS 2020 PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards CoRL 2020 PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals NeurIPS 2020 Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies ALT 2020 Planning in Markov Decision Processes with Gap-Dependent Sample Complexity NeurIPS 2020