Murphy, EoinEoinMurphyO'Neill, MichaelMichaelO'NeillBrabazon, AnthonyAnthonyBrabazon2012-02-212012-02-212011 ACM2011-07-12978-1-4503-0557-0http://hdl.handle.net/10197/3516Paper presented at the ACM Genetic and Evolutionary Computation Conference, GECCO 2011, 12-16 July, Dublin, IrelandThe lack of study of genetic programming in dynamic environments is recognised as a known issue in the field of genetic programming. This study compares the performance of two forms of genetic programming, grammatical evolution and a variation of grammatical evolution which uses tree-adjunct grammars, on a series of dynamic problems. Mean best fitness plots for the two representations are analysed and compared.1206169 bytesapplication/pdfenThis is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in the GECCO '11 Proceedings of the 13th annual conference companion on Genetic and evolutionary computation http://dx.doi.org/10.1145/2001576.2001763Genetic programmingGrammatical evolutionTree-adjunct grammarDynamic environmentsGenetic programming (Computer science)Evolutionary computationConference Publication10.1145/2001576.2001763https://creativecommons.org/licenses/by-nc-sa/1.0/