Policy Optimization Study Based on Evolutionary Learning

作     者：刘素平 丁永生 

作者机构：College of Information Science and TechnologyDonghua University Informatization OfficeDonghua University Engineering Research Center of Digitized Textile & Fashion TechnologyMinistry of EducationDonghua University 

出 版 物：《Journal of Donghua University(English Edition)》 (东华大学学报（英文版）)

年 卷 期：2009年第26卷第6期

页      面：621-624页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 081201[工学-计算机系统结构] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China(No.60534020) Cultivation Fund of the Key Scientific and Technical Innovation Project from Ministry of Education of China(No.706024) International Science Cooperation Foundation of Shanghai,China(No.061307041) 

主　　题：policy-based management evolution learning policy optimization 

摘      要：In order to achieve an intelligent and automated self-management network,dynamic policy configuration and selection are needed.A certain policy only suits to a certain network *** the network environment changes,the certain policy does not suit any ***,the policy-based management should also have similar natural selection *** policy will be retained,and policies which have lost their effectiveness are eliminated.A policy optimization method based on evolutionary learning was *** different shooting times,the priority of policy with high shooting times is improved,while policy with a low rate has lower priority,and long-term no shooting policy will be *** the strategy for the survival of the fittest is realized,and the degree of self-learning in policy management is improved.