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Reinforcement Learning for Linear Continuous-time Systems: an Incremental Learning Approach

Tao Bian Zhong-Ping Jiang

自动化学报（英文版）2019，Vol.6Issue(2)：433-440,8.

自动化学报（英文版）2019，Vol.6Issue(2)：433-440,8.DOI:10.1109/JAS.2019.1911390

Reinforcement Learning for Linear Continuous-time Systems: an Incremental Learning Approach

Tao Bian ¹Zhong-Ping Jiang²

作者信息

1. Bank of America Merrill Lynch, One Bryant Park, New York, NY 10036 USA
2. Control and Networks Lab, Department of Electrical and Computer Engineering, Tandon School of Engineering, New York University, 5 Metrotech Center, Brooklyn, NY 11201 USA
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摘要

关键词

Adaptive optimal control/robust dynamic programming/value iteration (Ⅵ)

Key words

Adaptive optimal control/robust dynamic programming/value iteration (Ⅵ)

引用本文复制引用

Tao Bian,Zhong-Ping Jiang..Reinforcement Learning for Linear Continuous-time Systems: an Incremental Learning Approach[J].自动化学报（英文版）,2019,6(2):433-440,8.

基金项目

The work was supported partially by the National Science Foundation (ECCS-1230040 and ECCS-1501044). （ECCS-1230040 and ECCS-1501044）

自动化学报（英文版）

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ISSN：2329-9266

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