McDermott, James and Galvan, 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:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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