- author = "Nicholas Freitag McPhee and Ellery Fussell Crane and Sara E. Lahr and Riccardo Poli",
- title = "Developmental plasticity in linear genetic programming",
- booktitle = "GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation",
- year = "2009",
- editor = "Guenther Raidl and Franz Rothlauf and Giovanni Squillero and Rolf Drechsler and Thomas Stuetzle and Mauro Birattari and Clare Bates Congdon and Martin Middendorf and Christian Blum and Carlos Cotta and Peter Bosman and Joern Grahl and Joshua Knowles and David Corne and Hans-Georg Beyer and Ken Stanley and Julian F. Miller and Jano {van Hemert} and Tom Lenaerts and Marc Ebner and Jaume Bacardit and Michael O'Neill and Massimiliano {Di Penta} and Benjamin Doerr and Thomas Jansen and Riccardo Poli and Enrique Alba",
- pages = "1019--1026",
- address = "Montreal",
- month = "8-12 " # jul,
- organisation = "SigEvo",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- note = "Nominated for best paper award in the GP track",
- keywords = "genetic algorithms, genetic programming, EDA",
- isbn13 = "978-1-60558-325-9",
-
DOI = "
doi:10.1145/1569901.1570039",
- size = "8 pages",
- abstract = "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.",
-
notes = "n-gram GP, 3 gram linear GP. Removed 2nd and first
order derived matrices by starting program with two
null operations. Program increases size by greedy
addition of blocks on instructions. Incremental blocks
need not be three instruction long. Symbolic
regression. Additional blocks added at random until
fitness is improved or time out.
One fixed (protected?) input register. ROUT different. memory with memory. {"}Does not scale well to large pools of constants{"} {"}IFD never hurts{"}
IFD solutions both {"}more complex{"} and {"}mode modular{"}
GECCO-2009 A joint meeting of the eighteenth international conference on genetic algorithms (ICGA-2009) and the fourteenth annual genetic programming conference (GP-2009).
ACM Order Number 910092. Also known as \cite{DBLP:conf/gecco/McPheeCLP09}",
