DocumentCode
419001
Title
The automatic generation of programs for classification problems with grammatical swarm
Author
O´Neill, Michael ; Brabazon, Anthony ; Adley, Catherine
Author_Institution
Biocomputing & Dev. Syst. Group, Univ. of Limerick, Ireland
Volume
1
fYear
2004
fDate
19-23 June 2004
Firstpage
104
Abstract
This case study examines the application of grammatical swarm to classification problems, and illustrates the particle swarm algorithms´ ability to specify the construction of programs. Each individual particle represents choices of program construction rules, where these rules are specified using a Backus-Naur Form grammar. Two problem instances are tackled, the first a mushroom classification problem, the second a bioinformatics problem that involves the detection of eukaryotic DNA promoter sequences. For the first problem we generate solutions that take the form of conditional statements in a C-like language subset, and for the second problem we generate simple regular expressions. The results demonstrate that it is simple regular expressions. The results demonstrate that it is possible to generate programs using the grammatical swarm technique with a performance similar to the grammatical evolution evolutionary automatic programming approach.
Keywords
automatic programming; evolutionary computation; grammars; optimisation; DNA promoter sequences; automatic program generation; bioinformatics problem; classification problems; evolutionary automatic programming; grammatical evolution; grammatical swarm; mushroom classification problem; particle swarm algorithm; program construction rules; Automatic programming; Birds; Control systems; DNA; Educational institutions; Insects; Marine animals; Particle swarm optimization; Robustness; Sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2004. CEC2004. Congress on
Print_ISBN
0-7803-8515-2
Type
conf
DOI
10.1109/CEC.2004.1330844
Filename
1330844
Link To Document