An investigation of the mutation operator using different representations in Grammatical Evolution
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- @InProceedings{Hugosson:2007:pliks,
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author = "Jonatan Hugosson and Erik Hemberg and
Anthony Brabazon and Michael O'Neill",
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title = "An investigation of the mutation operator using
different representations in Grammatical Evolution",
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booktitle = "2nd International Symposium {"}Advances in Artificial
Intelligence and Applications{"}",
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year = "2007",
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volume = "2",
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pages = "409--419",
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address = "Wisla, Poland",
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month = oct # " 15-17",
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keywords = "genetic algorithms, genetic programming, grammatical
evolution",
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ISSN = "1896 7094",
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URL = "http://www.proceedings2007.imcsit.org/pliks/45.pdf",
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abstract = "Grammatical evolution (GE) is a form of grammar-based
genetic programming. A particular feature of GE is that
it adopts a distinction between the genotype and
phenotype similar to that which exists in nature by
using a grammar to map between the genotype and
phenotype. This study seeks to extend our understanding
of GE by examining the impact of different genotypic
representations in order to determine whether certain
representations, and associated diversity-generation
operators, improve GE's efficiency and effectiveness.
Four mutation operators using two different
representations, binary and gray code representation
respectively, are investigated. The differing
combinations of representation and mutation operator
are tested on three benchmark problems. The results
provides support for the continued use of the standard
genotypic integer representation as the alternative
representations do not exhibit higher locality nor
better GE performance. The results raise the question
as to whether higher locality in GE actually improves
GE performance.",
- }
Genetic Programming entries for
Jonatan Hugosson
Erik Hemberg
Anthony Brabazon
Michael O'Neill
Citations