no code implementations • 12 Apr 2024 • Xuan Xie, Jiayang Song, Zhehua Zhou, Yuheng Huang, Da Song, Lei Ma
To bridge this gap, we conduct in this work a comprehensive evaluation of the effectiveness of existing online safety analysis methods on LLMs.
1 code implementation • 13 Sep 2023 • Jiayang Song, Zhehua Zhou, Jiawei Liu, Chunrong Fang, Zhan Shu, Lei Ma
Then, the performance of the reward function is assessed, and the results are presented back to the LLM for guiding its self-refinement process.
1 code implementation • 26 Aug 2023 • Zhehua Zhou, Jiayang Song, Kunpeng Yao, Zhan Shu, Lei Ma
Motivated by the substantial achievements observed in Large Language Models (LLMs) in the field of natural language processing, recent research has commenced investigations into the application of LLMs for complex, long-horizon sequential task planning challenges in robotics.
no code implementations • 10 Sep 2021 • Zhehua Zhou, Ozgur S. Oguz, Yi Ren, Marion Leibold, Martin Buss
Safe reinforcement learning aims to learn a control policy while ensuring that neither the system nor the environment gets damaged during the learning process.
no code implementations • 10 Jun 2020 • Cong Li, Qingchen Liu, Zhehua Zhou, Martin Buss, Fangzhou Liu
By introducing pseudo controls and risk-sensitive input and state penalty terms, the constrained robust stabilization problem of the original system is converted into an equivalent optimal control problem of an auxiliary system.