A Novel Artificial Neural Network Training Method Based on Quantum Computational Multi-Agent

Artificial Neural Networks are powerful tools that can be used to model and investigate various complex and non-linear phenomena.In this study,we constructed a new ANN based on Multi-Agent System(MAS) theory and quantum computing algorithm.All nodes in this new ANN were 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.