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Neural-network-based synchronous iteration learning method for multi-player zero-sum games

文献类型：期刊论文

作者Song, Ruizhuo1; Wei, Qinglai2; Song, Biao1
刊名NEUROCOMPUTING
出版日期2017-06-14
卷号242页码:73-82
关键词Adaptive Dynamic Programming Approximate Dynamic Programming Adaptive Critic Designs Multi-player Iteration Learning Neural Network
DOI10.1016/j.neucom.2017.02.051
文献子类Article
英文摘要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.
WOS关键词DISCRETE-TIME-SYSTEMS ; ADAPTIVE TRACKING CONTROL ; NONLINEAR-SYSTEMS ; POLICY ITERATION ; DEAD-ZONE ; DESIGN ; INPUT ; ALGORITHM
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000399859500007
资助机构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)
源URL[http://ir.ia.ac.cn/handle/173211/15265]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_智能化团队
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
推荐引用方式
GB/T 7714		 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.

入库方式： OAI收割

来源：自动化研究所

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