A novel Artificial Neural Network training method combined with Quantum Computational Multi-Agent System theory Online publication date: Sun, 25-Jan-2009
by Xiangping Meng, Jianzhong Wang, Yuzhen Pi, Quande Yuan
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 6, No. 1/2, 2009
Abstract: Artificial Neural Networks (ANNs) are powerful tools that can be used to model and investigate various complex and non-linear phenomena. In this study, we construct a new ANN, which is based on Multi-Agent System (MAS) theory and quantum computing algorithm. All nodes in this new ANN are presented as Quantum Computational (QC) agents, and these agents have learning ability. A novel ANN training method was proposed via implementing QCMAS reinforcement learning. This new ANN has powerful parallel-work ability and its training time is shorter than classic algorithm. Experiment results show that this method is effective.
Online publication date: Sun, 25-Jan-2009
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