DocumentCode :
1805589
Title :
A proposal of learning system with fuzzy rules under large environments
Author :
Hoshino, Yukinobu ; Kame, Katsuari
Author_Institution :
Dept. of Comput. Sci., Ritsumeikan Univ., Kyoto, Japan
Volume :
6
fYear :
1999
fDate :
36342
Firstpage :
4345
Abstract :
We show the problem and solution for intelligent systems under large environments. Intelligent systems, which are made from system of if-then rules, must support all cases for drive/control on any large environment. To get the specific professional intelligence, some studies of intelligent systems continue to try a learning system as the machine learning. Most learning systems use supervised learning. The supervised learning is accomplished by presenting training examples to a learning unit. In this paper, we will talk about unsupervised learning for dynamic and large environments. We tried chess as the dynamic and large environment and made chess´s algorithm as an intelligent system with unsupervised learning
Keywords :
fuzzy neural nets; fuzzy set theory; unsupervised learning; chess; fuzzy rules; if-then rules; intelligent systems; machine learning; unsupervised learning; Computer science; Fuzzy systems; Humans; Intelligent systems; Learning systems; Machine learning; Nonlinear equations; Proposals; Supervised learning; Unsupervised learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
ISSN :
1098-7576
Print_ISBN :
0-7803-5529-6
Type :
conf
DOI :
10.1109/IJCNN.1999.830867
Filename :
830867
Link To Document :
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