The use of version space controlled genetic algorithms to solve the Boole problem

Author

Reynolds, Robert G. ; Maletic, Jonathan I. ; Chang, Shan-Ping

Author_Institution

Dept. of Comput. Sci., Wayne State Univ., Detroit, MI, USA

fYear

1991

fDate

10-13 Nov 1991

Firstpage

14

Lastpage

21

Abstract

It is demonstrated that the VGA (version space guided genetic algorithm) is a particular instantiation of a more general class of systems, termed autonomous learning elements (ALEs). The basic components of an ALEs are discussed. The Boole problem posed by S. W. Wilson (1987) is introduced, and its expression in terms of the VGA framework is discussed. The details of the VGA system are given followed by a discussion of results. In particular, the performances of the VGA on two versions of the Boole problem are described and compared with those of classifier systems and decision trees

Keywords

genetic algorithms; learning systems; problem solving; Boole problem; VGA; autonomous learning elements; classifier systems; decision trees; version space controlled genetic algorithms; Biological cells; Computer science; Cultural differences; Degradation; Genetic algorithms; Genetic mutations; History; Problem-solving; Space exploration; Traveling salesman problems;

fLanguage

English

Publisher

ieee

Conference_Titel

Tools for Artificial Intelligence, 1991. TAI '91., Third International Conference on

Conference_Location

San Jose, CA

Print_ISBN

0-8186-2300-4

Type

conf

DOI

10.1109/TAI.1991.167071

Filename

167071