The ability of Genetic Programming to scale to problems of increasing difficulty operates on the premise that it is possible to capture regularities that exist in a problem environ...
Erik Hemberg, Conor Gilligan, Michael O'Neill, Ant...
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 f...
Abstract-- This work furthers the understanding of modularity in grammar-based genetic programming approaches by analyzing how different grammars may be capable of producing the sa...
When Genetic Programming is used to evolve arithmetic functions it often operates by composing them from a fixed collection of elementary operators and applying them to parameters...
This study examines the utility of meta-grammar constant generation on a series of benchmark problems. The performance of the meta-grammar approach is compared to a grammar which ...