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EUROGP
2007
Springer
135views Optimization» more  EUROGP 2007»
13 years 10 months ago
A Grammatical Genetic Programming Approach to Modularity in Genetic Algorithms
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...
EUROGP
2005
Springer
104views Optimization» more  EUROGP 2005»
13 years 10 months ago
mGGA: The meta-Grammar Genetic Algorithm
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...
Michael O'Neill, Anthony Brabazon
CEC
2010
IEEE
13 years 5 months ago
An examination on the modularity of grammars in grammatical evolutionary design
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...
John Mark Swafford, Michael O'Neill
GECCO
2006
Springer
218views Optimization» more  GECCO 2006»
13 years 8 months ago
Genetic programming with primitive recursion
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...
Stefan Kahrs
GECCO
2005
Springer
175views Optimization» more  GECCO 2005»
13 years 10 months ago
Meta-grammar constant creation with grammatical evolution by grammatical evolution
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 ...
Ian Dempsey, Michael O'Neill, Anthony Brabazon