most citedRobust Reinforcement Learning through Efficient Adversarial Herding

3 citations · 3 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2023★ 3 cited

Robust Reinforcement Learning through Efficient Adversarial Herding

Juncheng Dong, Hao-Lun Hsu, Qitong Gao +2

Although reinforcement learning (RL) is considered the gold standard for policy design, it may not always provide a robust solution in various scenarios. This can result in severe…

cs.RO2021

Improving Safety in Deep Reinforcement Learning using Unsupervised Action Planning

Hao-Lun Hsu, Qiuhua Huang, Sehoon Ha

One of the key challenges to deep reinforcement learning (deep RL) is to ensure safety at both training and testing phases. In this work, we propose a novel technique of unsupervis…