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	Data-based approximate policy iteration for affine nonlinear continuous-time optimal control design
	Luo, Biao; Wu, Huai-Ning; Huang, Tingwen; Liu, Derong
刊名	AUTOMATICA
	2014
卷号	50页码:3281-3290
关键词	Nonlinear optimal control Reinforcement learning Off-policy Data-based approximate policy iteration Neural network Hamilton-Jacobi-Bellman equation
ISSN号	0005-1098
DOI	10.1016/j.automatica.2014.10.056
URL标识	查看原文
收录类别	SCIE ; EI ; ESI高被引论文
WOS记录号	WOS:000347760100036
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/6548462
专题	北京航空航天大学
推荐引用方式 GB/T 7714	Luo, Biao,Wu, Huai-Ning,Huang, Tingwen,et al. Data-based approximate policy iteration for affine nonlinear continuous-time optimal control design[J]. AUTOMATICA,2014,50:3281-3290.
APA	Luo, Biao,Wu, Huai-Ning,Huang, Tingwen,&Liu, Derong.(2014).Data-based approximate policy iteration for affine nonlinear continuous-time optimal control design.AUTOMATICA,50,3281-3290.
MLA	Luo, Biao,et al."Data-based approximate policy iteration for affine nonlinear continuous-time optimal control design".AUTOMATICA 50(2014):3281-3290.

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