Fagan, DavidDavidFaganNicolau, MiguelMiguelNicolauO'Neill, MichaelMichaelO'NeillGalván-López, EdgarEdgarGalván-LópezBrabazon, AnthonyAnthonyBrabazonMcGarraghy, SeanSeanMcGarraghy2010-11-242010-11-242010 IEEE2010-07http://hdl.handle.net/10197/2579IEEE World Congress on Computational Intelligence, Barcelona, Spain, 18-23 July 2010We present an investigation into the genotype-phenotype map in Position Independent Grammatical Evolution (πGE). Previous studies have shown πGE to exhibit a performance increase over standard GE. The only difference between the two approaches is in how the genotype-phenotype mapping process is performed. GE uses a leftmost non terminal expansion, while πGE evolves the order of mapping as well as the content. In this study, we use the idea of focused search to examine which aspect of the πGE mapping process provides the lift in performance over standard GE by applying our approaches to four benchmark problems taken from specialised literature. We examined the traditional πGE approach and compared it to two setups which examined the extremes of mapping order search and content search, and against setups with varying ratios of content and order search. In all of these tests a purely content focused πGE was shown to exhibit a performance gain over the other setups.574350 bytesapplication/pdfenGrammatical evolutionMapping orderGenetic programmingEvolutionary computationGenetic programming (Computer science)Evolutionary computationConference Publication10.1109/CEC.2010.5586204https://creativecommons.org/licenses/by-nc-sa/1.0/