Improved value iteration for neural-network-based stochastic optimal control design
文献类型：期刊论文
| 作者 | Liang, Mingming2 ; Wang, Ding1,3; Liu, Derong4
|
| 刊名 | NEURAL NETWORKS
 |
| 出版日期 | 2020-04-01 |
| 卷号 | 124页码:280-295 |
| 关键词 | Adaptive critic designs Adaptive dynamic programming Neural networks Optimal control Stochastic processes Value iteration |
| ISSN号 | 0893-6080 |
| DOI | 10.1016/j.neunet.2020.01.004 |
| 通讯作者 | Wang, Ding(dingwang@bjut.edu.cn) |
| 英文摘要 | In this paper, a novel value iteration adaptive dynamic programming (ADP) algorithm is presented, which is called an improved value iteration ADP algorithm, to obtain the optimal policy for discrete stochastic processes. In the improved value iteration ADP algorithm, for the first time we propose a new criteria to verify whether the obtained policy is stable or not for stochastic processes. By analyzing the convergence properties of the proposed algorithm, it is shown that the iterative value functions can converge to the optimum. In addition, our algorithm allows the initial value function to be an arbitrary positive semi-definite function. Finally, two simulation examples are presented to validate the effectiveness of the developed method. (C) 2020 Elsevier Ltd. All rights reserved. |
| WOS关键词 | ALGORITHMS |
| 资助项目 | Beijing Natural Science Foundation, China[JQ19013] ; National Natural Science Foundation of China[61773373] ; National Natural Science Foundation of China[61533017] ; Youth Innovation Promotion Association of the Chinese Academy of Sciences |
| WOS研究方向 | Computer Science ; Neurosciences & Neurology |
| 语种 | 英语 |
| WOS记录号 | WOS:000518860600025 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| 资助机构 | Beijing Natural Science Foundation, China ; National Natural Science Foundation of China ; Youth Innovation Promotion Association of the Chinese Academy of Sciences |
| 源URL | [http://ir.ia.ac.cn/handle/173211/38630]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_智能化团队 |
| 通讯作者 | Wang, Ding |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 3.Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China 4.Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liang, Mingming,Wang, Ding,Liu, Derong. Improved value iteration for neural-network-based stochastic optimal control design[J]. NEURAL NETWORKS,2020,124:280-295. |
| APA | Liang, Mingming,Wang, Ding,&Liu, Derong.(2020).Improved value iteration for neural-network-based stochastic optimal control design.NEURAL NETWORKS,124,280-295. |
| MLA | Liang, Mingming,et al."Improved value iteration for neural-network-based stochastic optimal control design".NEURAL NETWORKS 124(2020):280-295. |
入库方式： OAI收割
来源：自动化研究所
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