CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 深度强化学习
Online reinforcement learning control by Bayesian inference
Xia, Zhongpu; Zhao, Dongbin; Dongbin Zhao
Source PublicationIET CONTROL THEORY AND APPLICATIONS
2016-08-08
Volume10Issue:12Pages:1331-1338
SubtypeArticle
AbstractReinforcement learning offers a promising way for self-learning control of an unknown system, but it involves the issues of policy evaluation and exploration, especially in the domain of continuous state. In this study, these issues are addressed from the perspective of probability. It models the action value function as the latent variable of Gaussian process, while the reward as the observed variable. Then an online approach is proposed to update the action value function by Bayesian inference. Taking an advantage of the proposed framework, a prior knowledge can be incorporated into the action value function, and thus an efficient exploration strategy is presented. At last, the Bayesian-state-action-reward-state-action algorithm is tested on some benchmark problems and empirical results show its effectiveness.
KeywordLearning Systems Bayes Methods Gaussian Processes Optimal Control Online Reinforcement Learning Control Bayesian Inference Self-learning Control Probability Action Value Function Gaussian Process Bayesian-state-action-reward-state-action Algorithm
WOS HeadingsScience & Technology ; Technology
DOI10.1049/iet-cta.2015.0669
WOS KeywordAFFINE NONLINEAR-SYSTEMS ; FEEDBACK-CONTROL ; TIME-SYSTEMS ; ALGORITHM ; ITERATION
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China (NSFC)(61273136 ; 61573353 ; 61533017)
WOS Research AreaAutomation & Control Systems ; Engineering ; Instruments & Instrumentation
WOS SubjectAutomation & Control Systems ; Engineering, Electrical & Electronic ; Instruments & Instrumentation
WOS IDWOS:000381410000003
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11432
Collection复杂系统管理与控制国家重点实验室_深度强化学习
Corresponding AuthorDongbin Zhao
AffiliationChinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Xia, Zhongpu,Zhao, Dongbin,Dongbin Zhao. Online reinforcement learning control by Bayesian inference[J]. IET CONTROL THEORY AND APPLICATIONS,2016,10(12):1331-1338.
APA Xia, Zhongpu,Zhao, Dongbin,&Dongbin Zhao.(2016).Online reinforcement learning control by Bayesian inference.IET CONTROL THEORY AND APPLICATIONS,10(12),1331-1338.
MLA Xia, Zhongpu,et al."Online reinforcement learning control by Bayesian inference".IET CONTROL THEORY AND APPLICATIONS 10.12(2016):1331-1338.
Files in This Item: Download All
File Name/Size DocType Version Access License
2016. IETCTA_XiaZhao(1559KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Xia, Zhongpu]'s Articles
[Zhao, Dongbin]'s Articles
[Dongbin Zhao]'s Articles
Baidu academic
Similar articles in Baidu academic
[Xia, Zhongpu]'s Articles
[Zhao, Dongbin]'s Articles
[Dongbin Zhao]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Xia, Zhongpu]'s Articles
[Zhao, Dongbin]'s Articles
[Dongbin Zhao]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 2016. IETCTA_XiaZhao.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.