Distilling the salient features of natural systems: Commentary on ``On the mapping of genotype to phenotype in evolutionary algorithms'' by Whigham, Dick and Maclaurin
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- @Article{O'Neill:2017:GPEM,
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author = "Michael O'Neill and Miguel Nicolau",
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title = "Distilling the salient features of natural systems:
Commentary on ``On the mapping of genotype to phenotype
in evolutionary algorithms'' by {Whigham, Dick and
Maclaurin}",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2017",
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volume = "18",
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number = "3",
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pages = "379--383",
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month = sep,
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note = "Special Peer Commentary on Mapping of Genotype to
Phenotype in Evolutionary Algorithms",
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keywords = "genetic algorithms, genetic programming, Grammatical
Evolution",
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ISSN = "1389-2576",
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DOI = "doi:10.1007/s10710-017-9293-0",
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size = "5 pages",
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abstract = "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
\cite{Whigham:2017:GPEM}. The authors present a
critical view on the use of genotype to phenotype
mapping in Evolutionary Algorithms, and how the use of
this analogy can be detrimental for problem solving.
They examine a grammar-based approach to Genetic
Programming (GP), Grammatical Evolution (GE), and
highlight properties of GE which are detrimental to
effective evolutionary search. Rather than use loose
analogies and methaphors, we suggest that a focus
should be (and has been in GE and other approaches to
GP) on addressing one of the most significant open
issues in our field, i.e., What are the sufficient set
of features in natural, genetic, evolutionary and
developmental systems, which can translate into the
most effective computational approaches for program
synthesis?",
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notes = "Introduction in \cite{Spector:2017:GPEM}
An author's reply to this comment is available at
http://dx.doi.org/10.1007/s10710-017-9289-9
\cite{Whigham:2017:GPEM2}.
This comment refers to the article available at:
http://dx.doi.org/10.1007/s10710-017-9288-x
\cite{Whigham:2017:GPEM}.",
- }
Genetic Programming entries for
Michael O'Neill
Miguel Nicolau
Citations