Methods

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 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 to Explore via Self-Supervised World Models ICML 2020 Planning with Abstract Learned Models While Learning Transferable Subtasks AAAI 2020 PLAS: Latent Action Space for Offline Reinforcement Learning CoRL 2020 Playing Atari with Six Neurons (Extended Abstract) IJCAI 2020 Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes AAAI 2020 Policy Improvement via Imitation of Multiple Oracles NeurIPS 2020 Policy learning in SE(3) action spaces CoRL 2020 Policy Learning of MDPs with Mixed Continuous/Discrete Variables: A Case Study on Model-Free Control of Markovian Jump Systems L4DC 2020 Policy Optimization for H_2 Linear Control with H_∞ Robustness Guarantee: Implicit Regularization and Global Convergence L4DC 2020 Policy Search by Target Distribution Learning for Continuous Control AAAI 2020 POMDPs in Continuous Time and Discrete Spaces NeurIPS 2020 Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework NeurIPS 2020 POPCORN: Partially Observed Prediction Constrained Reinforcement Learning AISTATS 2020 Population-Guided Parallel Policy Search for Reinforcement Learning ICLR 2020 Positive-Unlabeled Reward Learning CoRL 2020 POST: POlicy-Based Switch Tracking AAAI 2020 Potential Driven Reinforcement Learning for Hard Exploration Tasks IJCAI 2020 Practical Reinforcement Learning For MPC: Learning from sparse objectives in under an hour on a real robot L4DC 2020