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Adaptive Dynamic Programming for Discrete-Time Zero-Sum Games
Wei, Qinglai1,2; Liu, Derong3; Lin, Qiao1,2; Song, Ruizhuo3
Source PublicationIEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
2018-04-01
Volume29Issue:4Pages:957-969
SubtypeArticle
AbstractIn this paper, a novel adaptive dynamic programming (ADP) algorithm, called "iterative zero-sum ADP algorithm," is developed to solve infinite-horizon discrete-time two-player zero-sum games of nonlinear systems. The present iterative zero-sum ADP algorithm permits arbitrary positive semidefinite functions to initialize the upper and lower iterations. A novel convergence analysis is developed to guarantee the upper and lower iterative value functions to converge to the upper and lower optimums, respectively. When the saddle-point equilibrium exists, it is emphasized that both the upper and lower iterative value functions are proved to converge to the optimal solution of the zero-sum game, where the existence criteria of the saddle-point equilibrium are not required. If the saddle-point equilibrium does not exist, the upper and lower optimal performance index functions are obtained, respectively, where the upper and lower performance index functions are proved to be not equivalent. Finally, simulation results and comparisons are shown to illustrate the performance of the present method.
KeywordAdaptive Critic Designs Adaptive Dynamic Programming (Adp) Approximate Dynamic Programming Neurodynamic Programming Optimal Control Zero-sum Game
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TNNLS.2016.2638863
WOS KeywordOPTIMAL TRACKING CONTROL ; AFFINE NONLINEAR-SYSTEMS ; H-INFINITY CONTROL ; UNKNOWN DYNAMICS ; ITERATION ALGORITHM ; LEARNING ALGORITHM ; DIFFERENTIAL-GAMES ; FEEDBACK-CONTROL ; LINEAR-SYSTEMS ; CONTROL SCHEME
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000427859600016
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13627
Collection复杂系统管理与控制国家重点实验室_平行控制
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, 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
Wei, Qinglai,Liu, Derong,Lin, Qiao,et al. Adaptive Dynamic Programming for Discrete-Time Zero-Sum Games[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2018,29(4):957-969.
APA Wei, Qinglai,Liu, Derong,Lin, Qiao,&Song, Ruizhuo.(2018).Adaptive Dynamic Programming for Discrete-Time Zero-Sum Games.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,29(4),957-969.
MLA Wei, Qinglai,et al."Adaptive Dynamic Programming for Discrete-Time Zero-Sum Games".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 29.4(2018):957-969.
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