Grammatical Swarm: A Variable-Length Particle Swarm Algorithm

This study examines a variable-length Particle Swarm Algorithm for Social Programming. The Grammatical Swarm algorithm is a form of Social Programming as it uses Particle Swarm Optimisation, a social swarm algorithm, for the automatic generation of programs. This study extends earlier work on a fixed-length incarnation of Grammatical Swarm, where each individual particle represents choices of program construction rules, where these rules are specified using a Backus-Naur Form grammar. A selection of benchmark problems from the field of Genetic Programming are tackled and performance is compared to that of fixed-length Grammatical Swarm and of Grammatical Evolution. The results demonstrate that it is possible to successfully generate programs using a variable-length Particle Swarm Algorithm, however, based on the problems analysed it is recommended that the simpler bounded Grammatical Swarm be adopted.