Reinforcement Learning

Room-and-Object Aware Knowledge Reasoning for Remote Embodied Referring Expression CVPR 2021 Rough Terrain Navigation Using Divergence Constrained Model-Based Reinforcement Learning CoRL 2021 RRL: Resnet as representation for Reinforcement Learning ICML 2021 S3: Neural Shape, Skeleton, and Skinning Fields for 3D Human Modeling CVPR 2021 S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning in Robotics CoRL 2021 Safe Driving via Expert Guided Policy Optimization CoRL 2021 Safe Policy Iteration: A Monotonically Improving Approximate Policy Iteration Approach JMLR 2021 Safe Policy Optimization with Local Generalized Linear Function Approximations NeurIPS 2021 Safe Pontryagin Differentiable Programming NeurIPS 2021 Safe Reinforcement Learning by Imagining the Near Future NeurIPS 2021 Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks L4DC 2021 Safe Reinforcement Learning Using Advantage-Based Intervention ICML 2021 Safe Reinforcement Learning Using Robust Action Governor L4DC 2021 Safe Reinforcement Learning via Statistical Model Predictive Shielding RSS 2021 Safe Reinforcement Learning with Linear Function Approximation ICML 2021 Safe Reinforcement Learning with Natural Language Constraints NeurIPS 2021 Safety and Liveness Guarantees through Reach-Avoid Reinforcement Learning RSS 2021 SAINT-ACC: Safety-Aware Intelligent Adaptive Cruise Control for Autonomous Vehicles Using Deep Reinforcement Learning ICML 2021 Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms AISTATS 2021 Sample Complexity of Policy Gradient Finding Second-Order Stationary Points AAAI 2021 Sample-Efficient Automated Deep Reinforcement Learning ICLR 2021 Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games NeurIPS 2021 Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs with a Generative Model NeurIPS 2021 Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity ICML 2021 Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting NeurIPS 2021