DocumentCode :
2386581
Title :
Autonomic Learning Model and Algorithm Based on DFL
Author :
Wang, Jing ; Li, Fan-Zhang
Author_Institution :
Soochow Univ., Taipei
fYear :
2007
fDate :
2-4 Nov. 2007
Firstpage :
259
Lastpage :
259
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.
Keywords :
fuzzy logic; learning (artificial intelligence); autonomic learning model; conscious learning; dynamic fuzzy logic; independent learning; mechanical learning; passive learning; receptive learning; self-directed learning; Fuzzy logic; Fuzzy set theory; Learning systems; Logic functions; Machine learning; Machine learning algorithms; Multiagent systems; Predictive models; Problem-solving; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Granular Computing, 2007. GRC 2007. IEEE International Conference on
Conference_Location :
Fremont, CA
Print_ISBN :
978-0-7695-3032-1
Type :
conf
DOI :
10.1109/GrC.2007.71
Filename :
4403106
Link To Document :
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