mGGA: the meta-grammar genetic algorithm

Authors:
Michael O'Neill;Anthony Brabazon
Affiliations:
Department of Computer Science and Information Systems, University of Limerick, Ireland;Department of Accountancy, University College Dublin, Ireland
Venue:
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
Year:
2005

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Abstract

A novel Grammatical Genetic Algorithm, the meta-Grammar Genetic Algorithm (mGGA) is presented. The mGGA borrows a grammatical representation and the ideas of modularity and reuse from Genetic Programming, and in particular an evolvable grammar representation from Grammatical Evolution by Grammatical Evolution. We demonstrate its application to a number of benchmark problems where significant performance gains are achieved when compared to static grammars.