DocumentCode
2302245
Title
Toward a fuzzy government of genetic populations
Author
Arnone, S. ; Dell´Orto, M. ; Tettamanzi, A.
Author_Institution
Dipartimento di Scienze dell´´Informazione, Milan Univ., Italy
fYear
1994
fDate
6-9 Nov 1994
Firstpage
585
Lastpage
591
Abstract
Although genetic algorithms (GAs) are easy to implement and are powerful tools to solve difficult problems featuring huge search spaces, they usually require human supervision to be exploited successfully. It seems that fuzzy logic techniques can help reduce the amount of human intervention needed to use GAs. The paper concentrates on a particular application to symbolic regression to illustrate how to build a fuzzy knowledge-based system, or, to use a suggestive term, a fuzzy government, for GA control
Keywords
fuzzy logic; genetic algorithms; knowledge based systems; statistical analysis; GA control; fuzzy government; fuzzy knowledge-based system; fuzzy logic techniques; genetic algorithms; genetic populations; huge search spaces; human supervision; symbolic regression; Control systems; Cost function; Fuzzy control; Fuzzy systems; Genetic algorithms; Genetic mutations; Government; Humans; Knowledge based systems; Logic;
fLanguage
English
Publisher
ieee
Conference_Titel
Tools with Artificial Intelligence, 1994. Proceedings., Sixth International Conference on
Conference_Location
New Orleans, LA
Print_ISBN
0-8186-6785-0
Type
conf
DOI
10.1109/TAI.1994.346439
Filename
346439
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