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
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;
Conference_Titel :
Tools with Artificial Intelligence, 1994. Proceedings., Sixth International Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-8186-6785-0
DOI :
10.1109/TAI.1994.346439
