Neural-network-based synchronous iteration learning method for multi-player zero-sum games
Song, Ruizhuo1; Wei, Qinglai2; Song, Biao1
2017-06-14
发表期刊NEUROCOMPUTING
卷号242页码:73-82
文章类型Article
摘要In this paper, a synchronous solution method for multi-player zero-sum games without system dynamics is established based on neural network. The policy iteration (PI) algorithm is presented to solve the Hamilton-Jacobi-Bellman (HJB) equation. It is proven that the obtained iterative cost function is convergent to the optimal game value. For avoiding system dynamics, off-policy learning method is given to obtain the iterative cost function, controls and disturbances based on Pl. Critic neural network (CNN), action neural networks (ANNs) and disturbance neural networks (DNNs) are used to approximate the cost function, controls and disturbances. The weights of neural networks compose the synchronous weight matrix, and the uniformly ultimately bounded (UUB) of the synchronous weight matrix is proven. Two examples are given to show that the effectiveness of the proposed synchronous solution method for multi-player ZS games. (C) 2017 Elsevier B.V. All rights reserved.
关键词Adaptive Dynamic Programming Approximate Dynamic Programming Adaptive Critic Designs Multi-player Iteration Learning Neural Network
WOS标题词Science & Technology ; Technology
DOI10.1016/j.neucom.2017.02.051
关键词[WOS]DISCRETE-TIME-SYSTEMS ; ADAPTIVE TRACKING CONTROL ; NONLINEAR-SYSTEMS ; POLICY ITERATION ; DEAD-ZONE ; DESIGN ; INPUT ; ALGORITHM
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China(61304079 ; Fundamental Research Funds for the Central Universities(FRF-TP-15-056A3) ; Open Research Project from SKLMCCS(20150104) ; 61673054 ; 61374105)
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000399859500007
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/15265
专题复杂系统管理与控制国家重点实验室_平行控制
作者单位1.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
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Song, Ruizhuo,Wei, Qinglai,Song, Biao. Neural-network-based synchronous iteration learning method for multi-player zero-sum games[J]. NEUROCOMPUTING,2017,242:73-82.
APA Song, Ruizhuo,Wei, Qinglai,&Song, Biao.(2017).Neural-network-based synchronous iteration learning method for multi-player zero-sum games.NEUROCOMPUTING,242,73-82.
MLA Song, Ruizhuo,et al."Neural-network-based synchronous iteration learning method for multi-player zero-sum games".NEUROCOMPUTING 242(2017):73-82.
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