A comparison of GE and TAGE in dynamic environments

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Title: A comparison of GE and TAGE in dynamic environments
Authors: Murphy, Eoin
O'Neill, Michael
Brabazon, Anthony
Permanent link: http://hdl.handle.net/10197/3516
Date: 12-Jul-2011
Online since: 2012-02-21T15:23:48Z
Abstract: The 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.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: ACM
Copyright (published version): 2011 ACM
Keywords: Genetic programmingGrammatical evolutionTree-adjunct grammarDynamic environments
Subject LCSH: Genetic programming (Computer science)
Evolutionary computation
DOI: 10.1145/2001576.2001763
Other versions: http://dx.doi.org/10.1145/2001576.2001763
Language: en
Status of Item: Peer reviewed
Is part of: GECCO '11 : Proceedings of the 13th annual conference on Genetic and evolutionary computation
Conference Details: Paper presented at the ACM Genetic and Evolutionary Computation Conference, GECCO 2011, 12-16 July, Dublin, Ireland
ISBN: 978-1-4503-0557-0
Appears in Collections:Computer Science Research Collection
CASL Research Collection

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