A novel ANN model based on quantum computational MAS theory

Authors:
Xiangping Meng;Jianzhong Wang;Yuzhen Pi;Quande Yuan
Affiliations:
Department of Electrical Engineering, Changchun Institute of Technology, Changchun, Jilin Province, China;Department of Electrical Engineering, Changchun Institute of Technology, Changchun, Jilin Province, China;Department of Electrical Engineering, Changchun Institute of Technology, Changchun, Jilin Province, China;Department of Electrical Engineering, Changchun Institute of Technology, Changchun, Jilin Province, China
Venue:
LSMS'07 Proceedings of the Life system modeling and simulation 2007 international conference on Bio-Inspired computational intelligence and applications
Year:
2007

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Abstract

Artificial Neural Networks (ANNs) are powerful computational modeling tools, however there are still some limitations in ANNs. In this paper, we construct a new artificial neural network, which based on MAS theory and quantum computing algorithm. All nodes in this new ANN are presented as quantum computational (QC) agents, and these QC agents have learning ability via implementing reinforcement learning algorithm. This new ANN has powerful parallel-work ability and its training time is shorter than classic algorithm. Experiment results show this method is effective.