A network perspective on genotype-phenotype mapping in genetic programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.5772
- @Article{Hu:GPEM:gene-phen,
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author = "Ting Hu and Marco Tomassini and Wolfgang Banzhaf",
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title = "A network perspective on genotype-phenotype mapping in
genetic programming",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2020",
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volume = "21",
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number = "3",
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pages = "375--397",
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month = sep,
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note = "Special Issue: Highlights of Genetic Programming 2019
Events",
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keywords = "genetic algorithms, genetic programming, Evolvability,
Genotype phenotype map, Networks, Neutrality,
Redundancy, Robustness",
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ISSN = "1389-2576",
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DOI = "
doi:10.1007/s10710-020-09379-0",
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size = "23 pages",
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abstract = "Genotype phenotype mapping plays an essential role in
the design of an evolutionary algorithm. Variation
occurs at the genotypic level but fitness is evaluated
at the phenotypic level, therefore, this mapping
determines if and how variations are effectively
translated into quality improvements. In evolutionary
algorithms, this mapping has often been observed as
highly redundant, i.e., multiple genotypes can map to
the same phenotype, as well as heterogeneous, i.e.,
some phenotypes are represented by a large number of
genotypes while some phenotypes only have few. We
numerically study the redundant genotype-phenotype
mapping of a simple Boolean linear genetic programming
system and quantify the mutational connections among
phenotypes using tools of complex network analysis. The
analysis yields several interesting statistics of the
phenotype network. We show the evidence and provide
explanations for the observation that some phenotypes
are much more difficult to find as the target of a s",
- }
Genetic Programming entries for
Ting Hu
Marco Tomassini
Wolfgang Banzhaf
Citations