Share and Export
Share and Export
McDermott, James, 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
Preview
EG_a fine.pdf
Download (335kB) | Preview
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: | 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 |
| Related URLs: | |
| URI: | https://mural.maynoothuniversity.ie/id/eprint/15389 |
| 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 |
Repository Staff Only (login required)
- Item control page
Downloads
Downloads per month over past year
