The automatic generation of programs for classification problems with grammatical swarm
Michael O’Neill, Anthony Brabazon, Catherine C. Adley · 2004
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.