CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 深度强化学习
computational intelligence for changing environments
Amir,Hussain1; Dacheng,Tao2; Jonathan,Wu3; Zhao,Dongbin(赵冬斌)4
Source PublicationIEEE Computational Intelligence Magazine
2015-10-13
Volume11Issue:10(4)Pages:10-11
AbstractThe articles in this special section focus on the growing interest in biologically inspired learning (BIL), which refers to a wide range of learning techniques, motivated by biology, that try to mimic specific biological functions or behaviors.
KeywordBehavioral Science Guest Editorial Computational Intelligence
DOI10.1109/MCI.2015.2472119
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/19322
Collection复杂系统管理与控制国家重点实验室_深度强化学习
Affiliation1.University of Stirling, Scotland, UK
2.University of Technology, Sydney, AUSTRALIA
3.University of Windsor, Ontario, CANADA
4.Chinese Academy of Sciences, Beijing, CHINA
Recommended Citation
GB/T 7714
Amir,Hussain,Dacheng,Tao,Jonathan,Wu,et al. computational intelligence for changing environments[J]. IEEE Computational Intelligence Magazine,2015,11(10(4)):10-11.
APA Amir,Hussain,Dacheng,Tao,Jonathan,Wu,&Zhao,Dongbin.(2015).computational intelligence for changing environments.IEEE Computational Intelligence Magazine,11(10(4)),10-11.
MLA Amir,Hussain,et al."computational intelligence for changing environments".IEEE Computational Intelligence Magazine 11.10(4)(2015):10-11.
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