Implementation of a genetic algorithm based associative classifier system (ACS)

Author

Twardowski, Kirk E.

Author_Institution

Syracuse Univ., NY, USA

fYear

1990

fDate

6-9 Nov 1990

Firstpage

48

Lastpage

54

Abstract

The first results from the development of a genetic algorithm-based ACS are presented. The ACS is a result of mapping the inherent parallelism in classifier systems to a program which executes on a PC-based associative processor. The associative algorithms of the ACS for the coherent processor are presented. It is demonstrated that this associative implementation of the BOOLE classifier system learns as well as results published for serial implementations. It is shown that the use of an associative processor as a co-processor can decrease classifier system response time, particularly for classifier systems with a large number of rules. In fact, when the number of rules in the ACS was increased by an order of magnitude, the response time of the system increased only 25% after DOS overhead was removed

Keywords

classification; content-addressable storage; genetic algorithms; microcomputer applications; parallel algorithms; pattern recognition; BOOLE classifier system; PC-based associative processor; associative algorithms; classifier system response time; classifier systems; coherent processor; genetic algorithm based associative classifier system; genetic algorithm-based ACS; inherent parallelism; serial implementations; CADCAM; Computer aided manufacturing; Computer architecture; Coprocessors; Delay; Genetic algorithms; Hardware; Kirk field collapse effect; Parallel processing; Real time systems;

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.1990.130308

Filename

130308