4 papers
Augmented Lagrangian Method for Last-Iterate Convergence for Constrained MDPs
Michael Lu, Max Qiushi Lin, Mo Chen +1
We study policy optimization for infinite-horizon, discounted constrained Markov decision processes (CMDPs). While existing theoretical guarantees typically hold for the mixture po…
Fast Confidence-Aware Human Prediction via Hardware-accelerated Bayesian Inference for Safe Robot Navigation
Michael Lu, Minh Bui, Xubo Lyu +1
As robots increasingly integrate into everyday environments, ensuring their safe navigation around humans becomes imperative. Efficient and safe motion planning requires robots to…
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…
Task-Oriented Koopman-Based Control with Contrastive Encoder
Xubo Lyu, Hanyang Hu, Seth Siriya +2
We present task-oriented Koopman-based control that utilizes end-to-end reinforcement learning and contrastive encoder to simultaneously learn the Koopman latent embedding, operato…