Personalized robotic control via constrained multi-objective reinforcement learning

• Main Authors: He, Xiangkun, Hu, Zhongxu, Yang, Haohan, Lv, Chen
• 其他作者: School of Mechanical and Aerospace Engineering
• 格式: Article
• 語言: English
• 出版: 2024
• 主題: Engineering::Mechanical engineering; Reinforcement Learning; Multi-Objective Optimization
• 在線閱讀: https://hdl.handle.net/10356/173290

Reinforcement learning is capable of providing state-of-art performance in end-to-end robotic control tasks. Nevertheless, many real-world control tasks necessitate the balancing of multiple conflicting objectives while simultaneously ensuring that the learned policies adhere to constraints. Additio...