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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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A Reply to this article was published on 24 February 2017

The Original Article was published on 23 February 2017

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. 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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Authors and Affiliations

  1. School of Business, University College Dublin, Dublin, Ireland

    Michael O’Neill & Miguel Nicolau

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  1. Michael O’Neill
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  2. Miguel Nicolau
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Correspondence to Michael O’Neill.

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O’Neill, M., Nicolau, M. Distilling the salient features of natural systems: Commentary on “On the mapping of genotype to phenotype in evolutionary algorithms” by Whigham, Dick and Maclaurin. Genet Program Evolvable Mach 18, 379–383 (2017). https://doi.org/10.1007/s10710-017-9293-0

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