Trust-region inverse reinforcement learning
This paper proposes a new unified inverse reinforcement learning (IRL) framework based on trust-region methods and a recently proposed Pontryagin differential programming (PDP) method in Jin et al. (2020), which aims to learn the parameters in both the system model and the cost function for three ty...
Saved in:
Main Authors: | Cao, Kun, Xie, Lihua |
---|---|
其他作者: | School of Electrical and Electronic Engineering |
格式: | Article |
語言: | English |
出版: |
2023
|
主題: | |
在線閱讀: | https://hdl.handle.net/10356/170705 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
相似書籍
-
Game-theoretic inverse reinforcement learning: a differential pontryagin's maximum principle approach
由: Cao, Kun, et al.
出版: (2022) -
An efficient spectral trust-region deflation method for multiple solutions
由: Li, Lin, et al.
出版: (2023) -
A trust region algorithm for minimization of locally Lipschitzian functions
由: Qi, L., et al.
出版: (2013) -
Trust region methods for solving multiobjective optimisation
由: Qu, S., et al.
出版: (2014) -
On piecewise quadratic Newton and trust region problems
由: Sun, J.
出版: (2013)