Game-theoretic inverse reinforcement learning: a differential pontryagin's maximum principle approach

This paper proposes a game-theoretic inverse reinforcement learning (GT-IRL) framework, which aims to learn the parameters in both the dynamic system and individual cost function of multistage games from demonstrated trajectories. Different from the probabilistic approaches in computer science commu...

全面介紹

Saved in:
書目詳細資料
Main Authors: Cao, Kun, Xie, Lihua
其他作者: School of Electrical and Electronic Engineering
格式: Article
語言:English
出版: 2022
主題:
在線閱讀:https://hdl.handle.net/10356/162585
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
機構: Nanyang Technological University
語言: English

相似書籍