A genetics-based technique for the automated acquisition of expert system rule bases

Author

Johnson, Clayton M. ; Feyock, Stefan

Author_Institution

Dept. of Comput. Sci., Coll. of William & Mary, Williamsburg, VA, USA

fYear

1991

fDate

30 Sep-2 Oct 1991

Firstpage

78

Lastpage

82

Abstract

The genetic algorithm (GA) is a powerful search paradigm which combines elements from evolutionary biology with concepts from population genetics. Because they operate in a domain-independent fashion, GAs have been successfully applied to a wide variety of optimization and learning problems. A technique is presented by which genetic algorithms can be adapted to operate upon the LISP-like production rules typically used in expert systems. A brief overview is presented of genetic algorithms and genetics-based learning

Keywords

expert systems; genetic algorithms; knowledge acquisition; learning systems; LISP-like production rules; domain-independent; evolutionary biology; expert systems; genetic algorithm; genetics-based learning; learning problems; optimization; population genetics; rule-base acquisition; search paradigm; Artificial intelligence; Biology; Computer science; Diagnostic expert systems; Educational institutions; Evolution (biology); Expert systems; Genetic algorithms; Learning; Organisms;

fLanguage

English

Publisher

ieee

Conference_Titel

Developing and Managing Expert System Programs, 1991., Proceedings of the IEEE/ACM International Conference on

Conference_Location

Washington, DC

Print_ISBN

0-8186-2250-4

Type

conf

DOI

10.1109/DMESP.1991.171705

Filename

171705