Applications

Planning to Explore via Self-Supervised World Models ICML 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 learning in SE(3) action spaces CoRL 2020 Policy Search by Target Distribution Learning for Continuous Control AAAI 2020 Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement Learning ICML 2020 POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis NeurIPS 2020 POMDPs in Continuous Time and Discrete Spaces NeurIPS 2020 POMO: Policy Optimization with Multiple Optima for Reinforcement Learning NeurIPS 2020 Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework NeurIPS 2020 POPCORN: Partially Observed Prediction Constrained Reinforcement Learning AISTATS 2020 Positive-Unlabeled Reward Learning CoRL 2020 Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes AISTATS 2020 Practical Reinforcement Learning For MPC: Learning from sparse objectives in under an hour on a real robot L4DC 2020 Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control ICML 2020 Probably Approximately Correct Vision-Based Planning using Motion Primitives CoRL 2020 Production-based Cognitive Models as a Test Suite for Reinforcement Learning Algorithms EMNLP 2020 Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits NeurIPS 2020 Proximal Distilled Evolutionary Reinforcement Learning AAAI 2020 Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping RSS 2020 Ready Policy One: World Building Through Active Learning ICML 2020 Real World Games Look Like Spinning Tops NeurIPS 2020 Rebalancing Expanding EV Sharing Systems with Deep Reinforcement Learning IJCAI 2020 Reducing Sampling Error in Batch Temporal Difference Learning ICML 2020