Methods

DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames ICLR 2020 Decentralized MCTS via Learned Teammate Models IJCAI 2020 Decentralized TD Tracking with Linear Function Approximation and its Finite-Time Analysis NeurIPS 2020 Deep Conservative Policy Iteration AAAI 2020 Deep Coordination Graphs ICML 2020 Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space CoRL 2020 Deep Model-Based Reinforcement Learning via Estimated Uncertainty and Conservative Policy Optimization AAAI 2020 Deep PQR: Solving Inverse Reinforcement Learning using Anchor Actions ICML 2020 Deep Reactive Planning in Dynamic Environments CoRL 2020 Deep Reinforcement and InfoMax Learning NeurIPS 2020 Deep Reinforcement Learning for Active Human Pose Estimation AAAI 2020 Deep Reinforcement Learning for Closed-Loop Blood Glucose Control MLHC 2020 Deep Reinforcement Learning for General Game Playing AAAI 2020 Deep Reinforcement Learning for Organ Localization in CT MIDL 2020 Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous Control CoRL 2020 Deep Reinforcement Learning with Robust and Smooth Policy ICML 2020 Deep Symbolic Superoptimization Without Human Knowledge ICLR 2020 DeepWeave: Accelerating Job Completion Time with Deep Reinforcement Learning-based Coflow Scheduling IJCAI 2020 Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems JMLR 2020 Designing Optimal Dynamic Treatment Regimes: A Causal Reinforcement Learning Approach ICML 2020 Determining the Possibility of Transfer Learning in Deep Reinforcement Learning Using Grad-CAM (Student Abstract) AAAI 2020 Deterministic Value-Policy Gradients AAAI 2020 Dialog State Tracking with Reinforced Data Augmentation AAAI 2020 Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces NeurIPS 2020 Disagreement-Regularized Imitation Learning ICLR 2020