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Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Ding Wang Ning Gao Derong Liu Jinna Li Frank L.Lewis

自动化学报（英文版）2024，Vol.11Issue(1)：18-36,19.
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自动化学报（英文版）2024，Vol.11Issue(1)：18-36,19.DOI:10.1109/JAS.2023.123843

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Ding Wang 1Ning Gao 1Derong Liu 2Jinna Li 3Frank L.Lewis4

作者信息

  • 1. Faculty of Information Technology,Beijing Key Laboratory of Computational Intelligence and Intelligent System,Beijing Laboratory of Smart Environmental Protection,and Beijing Institute of Artificial Intelligence,Beijing University of Technology,Beijing 100124,China
  • 2. School of System Design and Intelligent Manufacturing,Southern University of Science and Technology,Shenzhen 518055,China,and also with the Department of Electrical and Computer Engineering,University of Illinois at Chicago,Chicago IL 60607 USA
  • 3. School of Information and Control Engineering,Liaoning Petrochemical University,Fushun 113001,China
  • 4. UTA Research Institute,the University of Texas at Arlington,Arlington TX 76118 USA
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摘要

关键词

Adaptive dynamic programming(ADP)/advanced control/complex environment/data-driven control/event-triggered design/intelligent control/neural networks/nonlinear systems/opti-mal control/reinforcement learning(RL)

Key words

Adaptive dynamic programming(ADP)/advanced control/complex environment/data-driven control/event-triggered design/intelligent control/neural networks/nonlinear systems/opti-mal control/reinforcement learning(RL)

引用本文复制引用

Ding Wang,Ning Gao,Derong Liu,Jinna Li,Frank L.Lewis..Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications[J].自动化学报（英文版）,2024,11(1):18-36,19.

基金项目

This work was supported in part by the National Natural Science Foundation of China(62222301,62073085,62073158,61890930-5,62021003),the National Key Research and Development Program of China(2021ZD0112302,2021 ZD 0112301,2018YFC1900800-5),and Beijing Natural Science Foundation(JQ19013). （62222301,62073085,62073158,61890930-5,62021003）

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