Title :
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
fDate :
30 Sep-2 Oct 1991
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;
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
DOI :
10.1109/DMESP.1991.171705
