{"title":"Autonomic Learning Model and Algorithm Based on DFL","authors":"Jing Wang, Fanzhang Li","doi":"10.1109/GrC.2007.71","DOIUrl":null,"url":null,"abstract":"Autonomic learning (AL) refers to an inner mechanism of self-directed learning integrated by learner's attitude, capability and learning strategy. AL usually means active, self-conscious and independent learning, which is opposite to the type of passive, mechanical or receptive learning. AL has always been a hot issue of machine learning research. In this paper, based on the theory of dynamic fuzzy logic (DFL), autonomic learning model and algorithm are developed, which provide a theoretical basis for the people to solve this type of problem. Simulation results illustrate the efficiency of this autonomic learning method.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International Conference on Granular Computing (GRC 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GrC.2007.71","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Autonomic learning (AL) refers to an inner mechanism of self-directed learning integrated by learner's attitude, capability and learning strategy. AL usually means active, self-conscious and independent learning, which is opposite to the type of passive, mechanical or receptive learning. AL has always been a hot issue of machine learning research. In this paper, based on the theory of dynamic fuzzy logic (DFL), autonomic learning model and algorithm are developed, which provide a theoretical basis for the people to solve this type of problem. Simulation results illustrate the efficiency of this autonomic learning method.