%0 Journal Article
%T Multi-Agent system for information filtering based on hybrid learning approach<br>基于混合学习策略的多Agent信息过滤系统
%A FEI Hong-xiao
%A GONG Yan-ling
%A XIE Wen-biao
%A NI Min
%A <br>费洪晓
%A 巩艳玲
%A 谢文彪
%A 倪敏
%J 计算机应用
%D 2006
%I 
%X 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.
%K Agent<br>个性化信息过滤
%K 强化学习
%K BP神经网络
%K 蒙特卡罗算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=A0DBEFD770AC6945&yid=37904DC365DD7266&vid=96C778EE049EE47D&iid=0B39A22176CE99FB&sid=866F8A6B640835A7&eid=8DC3E99E16EDAC8C&journal_id=1001-9081&journal_name=计算机应用&referenced_num=5&reference_num=6