Multi-Agent system for information filtering based on hybrid learning approach
基于混合学习策略的多Agent信息过滤系统

With the requirement of user's specific information service,a framework of multi-Agent system for information filtering,based on hybrid learning approach and BP neural network,was proposed in this paper.This system aimed at helping the user obtain the relevant information precisely.The Modified Monte-Carlo method was used to collaborate multi-Agent system,and the intelligent Agent was exploited to watch the user's behaviors.Besides,the BP neural network was applied to learn the user's interests in this system.A conclusion is drawn that this system is able to obtain the user's interests precisely without the user's repeatedly feedback,so as to reduce the labor of the user.