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    A Fine-Grained View of GP Locality with Binary Decision Diagrams as Ant Phenotypes


    McDermott, James and Galván, Edgar and O'Neill, Michael (2010) A Fine-Grained View of GP Locality with Binary Decision Diagrams as Ant Phenotypes. Parallel Problem Solving from Nature – PPSN XIV, 6238. pp. 164-173. ISSN 0302-9743

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    Abstract

    The property that neighbouring genotypes tend to map to neighbouring phenotypes, i.e. locality, is an important criterion in the study of problem difficulty. Locality is problematic in tree-based genetic programming (GP), since typically there is no explicit phenotype. Here, we define multiple phenotypes for the artificial ant problem, and use them to describe a novel fine-grained view of GP locality. This allows us to identify the mapping from an ant’s behavioural phenotype to its concrete path as being inherently non-local, and show that therefore alternative genetic encodings and operators cannot make the problem easy. We relate this to the results of evolutionary runs.

    Item Type: Article
    Keywords: Genetic programming; phenotype; locality; problem difficulty; artificial ant;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 15389
    Identification Number: https://doi.org/10.1007/978-3-642-15844-5_17
    Depositing User: Edgar Galvan
    Date Deposited: 01 Feb 2022 15:15
    Journal or Publication Title: Parallel Problem Solving from Nature – PPSN XIV
    Publisher: Springer
    Refereed: Yes
    URI:

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