Genotype–phenotype mapping implications for genetic programming representation: commentary on “On the mapping of genotype to phenotype in evolutionary algorithms” by Peter A. Whigham, Grant Dick, and James Maclaurin

Research output: Contribution to journalComment/debate

Abstract

This comment refers to the article available at doi:10.1007/s10710-017-9288-x. Here we comment on the article “On the mapping of genotype to phenotype in evolutionary algorithms,” by Peter A. Whigham, Grant Dick, and James Maclaurin. The article reasons about analogies from molecular biology to evolutionary algorithms and discusses conditions for biological adaptations in the context of grammatical evolution, which provide a useful perspective to GP practitioners. However, the connection of the listed implications for GP is not sufficiently convincing for the reader . Therefore this commentary will (1) examine the proposed principles one by one, challenging the authors to provide more supporting evidence where felt that this was needed, and (2) propose a methodical way to GP practitioners to apply these principles when designing GP representations.

LanguageEnglish
JournalGenetic Programming and Evolvable Machines
Volumein press
Early online date24 Feb 2017
DOIs
Publication statusE-pub ahead of print - 24 Feb 2017

Fingerprint

Genetic programming
Genotype
Genetic Programming
Phenotype
Evolutionary algorithms
Evolutionary Algorithms
Grammatical Evolution
Molecular biology
Molecular Biology
Analogy
Context
Evidence

Bibliographical note

© The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Keywords

  • genotype–phenotype mapping
  • practical guidelines for GP representation design
  • representation

Cite this

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title = "Genotype–phenotype mapping implications for genetic programming representation: commentary on “On the mapping of genotype to phenotype in evolutionary algorithms” by Peter A. Whigham, Grant Dick, and James Maclaurin",
abstract = "This comment refers to the article available at doi:10.1007/s10710-017-9288-x. Here we comment on the article “On the mapping of genotype to phenotype in evolutionary algorithms,” by Peter A. Whigham, Grant Dick, and James Maclaurin. The article reasons about analogies from molecular biology to evolutionary algorithms and discusses conditions for biological adaptations in the context of grammatical evolution, which provide a useful perspective to GP practitioners. However, the connection of the listed implications for GP is not sufficiently convincing for the reader . Therefore this commentary will (1) examine the proposed principles one by one, challenging the authors to provide more supporting evidence where felt that this was needed, and (2) propose a methodical way to GP practitioners to apply these principles when designing GP representations.",
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AB - This comment refers to the article available at doi:10.1007/s10710-017-9288-x. Here we comment on the article “On the mapping of genotype to phenotype in evolutionary algorithms,” by Peter A. Whigham, Grant Dick, and James Maclaurin. The article reasons about analogies from molecular biology to evolutionary algorithms and discusses conditions for biological adaptations in the context of grammatical evolution, which provide a useful perspective to GP practitioners. However, the connection of the listed implications for GP is not sufficiently convincing for the reader . Therefore this commentary will (1) examine the proposed principles one by one, challenging the authors to provide more supporting evidence where felt that this was needed, and (2) propose a methodical way to GP practitioners to apply these principles when designing GP representations.

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