2 papers
cs.RO2024
Learning Robust Policies via Interpretable Hamilton-Jacobi Reachability-Guided Disturbances
Hanyang Hu, Xilun Zhang, Xubo Lyu +1
Deep Reinforcement Learning (RL) has shown remarkable success in robotics with complex and heterogeneous dynamics. However, its vulnerability to unknown disturbances and adversaria…
cs.RO2019
TTR-Based Reward for Reinforcement Learning with Implicit Model Priors
Xubo Lyu, Mo Chen
Model-free reinforcement learning (RL) is a powerful approach for learning control policies directly from high-dimensional state and observation. However, it tends to be data-ineff…