TY - GEN
T1 - Developmental plasticity in linear genetic programming
AU - McPhee, Nic
AU - Crane, Ellery
AU - Lahr, Sara E.
AU - Poli, Riccardo
PY - 2009
Y1 - 2009
N2 - Biological organisms exhibit numerous types of plasticity, where they respond both developmentally and behaviorally to environmental factors. In some organisms, for example, environmental conditions can lead to the developmental expression of genes that would otherwise remain dormant, leading to significant phenotypic variation and allowing selection to act on these otherwise "invisible" genes. In contrast to biological plasticity, the vast majority of evolutionary computation systems, including genetic programming, are rigid and can only adapt to very limited external changes. In this paper we extend the N-gram GP system, a recently introduced estimation of distribution algorithm for program evolution, using Incremental Fitness-based Development (IFD), a novel technique which allows for developmental plasticity in the generation of linear-GP style programs. Tests with a large set of problems show that the new system outperforms the original N-gram GP system and is competitive with standard GP. Analysis of the evolved programs indicates that IFD allows for the generation of more complex programs than standard N-gram GP, with the generated programs often containing several separate sequences of instructions that are reused multiple times, often with variations.
AB - Biological organisms exhibit numerous types of plasticity, where they respond both developmentally and behaviorally to environmental factors. In some organisms, for example, environmental conditions can lead to the developmental expression of genes that would otherwise remain dormant, leading to significant phenotypic variation and allowing selection to act on these otherwise "invisible" genes. In contrast to biological plasticity, the vast majority of evolutionary computation systems, including genetic programming, are rigid and can only adapt to very limited external changes. In this paper we extend the N-gram GP system, a recently introduced estimation of distribution algorithm for program evolution, using Incremental Fitness-based Development (IFD), a novel technique which allows for developmental plasticity in the generation of linear-GP style programs. Tests with a large set of problems show that the new system outperforms the original N-gram GP system and is competitive with standard GP. Analysis of the evolved programs indicates that IFD allows for the generation of more complex programs than standard N-gram GP, with the generated programs often containing several separate sequences of instructions that are reused multiple times, often with variations.
KW - Development
KW - Genetic programming
KW - N-grams
KW - Plasticity
UR - http://www.scopus.com/inward/record.url?scp=72749104383&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=72749104383&partnerID=8YFLogxK
U2 - 10.1145/1569901.1570039
DO - 10.1145/1569901.1570039
M3 - Conference contribution
AN - SCOPUS:72749104383
SN - 9781605583259
T3 - Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
SP - 1019
EP - 1026
BT - Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
T2 - 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
Y2 - 8 July 2009 through 12 July 2009
ER -