CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 深度强化学习
Convergence Proof of Approximate Policy Iteration for Undiscounted Optimal Control of Discrete-Time Systems
Zhu, Yuanheng1; Zhao, Dongbin1; He, Haibo2; Ji, Junhong3
Source PublicationCOGNITIVE COMPUTATION
2015-12-01
Volume7Issue:6Pages:763-771
SubtypeArticle
AbstractApproximate policy iteration (API) is studied to solve undiscounted optimal control problems in this paper. A discrete-time system with the continuous-state space and the finite-action set is considered. As approximation technique is used for the continuous-state space, approximation errors exist in the calculation and disturb the convergence of the original policy iteration. In our research, we analyze and prove the convergence of API for undiscounted optimal control. We use an iterative method to implement approximate policy evaluation and demonstrate that the error between approximate and exact value functions is bounded. Then, with the finite-action set, the greedy policy in policy improvement is generated directly. Our main theorem proves that if a sufficiently accurate approximator is used, API converges to the optimal policy. For implementation, we introduce a fuzzy approximator and verify the performance on the puddle world problem.
KeywordApproximate Policy Iteration Approximation Error Optimal Control Fuzzy Approximator
WOS HeadingsScience & Technology ; Technology ; Life Sciences & Biomedicine
DOI10.1007/s12559-015-9350-z
WOS KeywordNONLINEAR-SYSTEMS ; FEEDBACK-CONTROL ; MOBILE ROBOTS ; ALGORITHM
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61273136) ; State Key Laboratory of Robotics and System(SKLRS-2015-ZD-04) ; National Science Foundation (NSF)(ECCS 1053717)
WOS Research AreaComputer Science ; Neurosciences & Neurology
WOS SubjectComputer Science, Artificial Intelligence ; Neurosciences
WOS IDWOS:000366329200012
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/10525
Collection复杂系统管理与控制国家重点实验室_深度强化学习
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Rhode Isl, Dept Elect Comp & Biomed Engn, Kingston, RI 02881 USA
3.Harbin Inst Technol, State Key Lab Robot & Syst, Harbin 150001, Peoples R China
Recommended Citation
GB/T 7714
Zhu, Yuanheng,Zhao, Dongbin,He, Haibo,et al. Convergence Proof of Approximate Policy Iteration for Undiscounted Optimal Control of Discrete-Time Systems[J]. COGNITIVE COMPUTATION,2015,7(6):763-771.
APA Zhu, Yuanheng,Zhao, Dongbin,He, Haibo,&Ji, Junhong.(2015).Convergence Proof of Approximate Policy Iteration for Undiscounted Optimal Control of Discrete-Time Systems.COGNITIVE COMPUTATION,7(6),763-771.
MLA Zhu, Yuanheng,et al."Convergence Proof of Approximate Policy Iteration for Undiscounted Optimal Control of Discrete-Time Systems".COGNITIVE COMPUTATION 7.6(2015):763-771.
Files in This Item: Download All
File Name/Size DocType Version Access License
art%3A10.1007%2Fs125(809KB)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
[Zhu, Yuanheng]'s Articles
[Zhao, Dongbin]'s Articles
[He, Haibo]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhu, Yuanheng]'s Articles
[Zhao, Dongbin]'s Articles
[He, Haibo]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhu, Yuanheng]'s Articles
[Zhao, Dongbin]'s Articles
[He, Haibo]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: art%3A10.1007%2Fs12559-015-9350-z.pdf
Format: Adobe PDF
This file does not support browsing at this time
All comments (0)
No comment.
 

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