DocumentCode
3052244
Title
The control of genetic algorithms using version spaces
Author
Reynolds, Robert G.
Author_Institution
Dept. of Comput. Sci., Wayne State Univ., Detroit, MI, USA
fYear
1990
fDate
6-9 Nov 1990
Firstpage
342
Lastpage
348
Abstract
It is demonstrated how the traditional genetic algorithm (GA) can be augmented by incorporating domain knowledge in the form of a version space (VS) into the structure. This hybrid inductive learning system is designed to handle problems in concept learning using the VS to control the search process that is performed by the GA. In this hybrid system a novel class of schemata is present called the hyperschema. A theorem for the hyperschema analogous to that for the traditional schema is presented. This theorem demonstrates how the addition of domain knowledge in the form of a VS allows the hybrid system to exploit schemata of higher order and defining length via a hitchhiking effect
Keywords
artificial intelligence; genetic algorithms; learning systems; concept learning; domain knowledge; genetic algorithms; hitchhiking effect; hybrid inductive learning system; hyperschema; version space; version spaces; Algorithm design and analysis; Biological cells; Computer science; Control systems; Cultural differences; Genetic algorithms; Learning systems; Problem-solving; Process control; Traveling salesman problems;
fLanguage
English
Publisher
ieee
Conference_Titel
Tools for Artificial Intelligence, 1990.,Proceedings of the 2nd International IEEE Conference on
Conference_Location
Herndon, VA
Print_ISBN
0-8186-2084-6
Type
conf
DOI
10.1109/TAI.1990.130360
Filename
130360
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