- author = "Markus Brameier and Wolfgang Banzhaf",
- title = "Neutral Variations Cause Bloat in Linear GP",
- booktitle = "Genetic Programming, Proceedings of EuroGP'2003",
- year = "2003",
- editor = "Conor Ryan and Terence Soule and Maarten Keijzer and Edward Tsang and Riccardo Poli and Ernesto Costa",
- volume = "2610",
- series = "LNCS",
- pages = "286--296",
- address = "Essex",
- publisher_address = "Berlin",
- month = "14-16 " # apr,
- organisation = "EvoNet",
- publisher = "Springer-Verlag",
- keywords = "genetic algorithms, genetic programming: Poster",
- ISBN = "3-540-00971-X",
-
DOI = "
doi:10.1007/3-540-36599-0_26",
- abstract = "In this contribution we investigate the influence of different variation effects on the growth of code. A mutation-based variant of linear GP is applied that operates with minimum structural step sizes. Results show that neutral variations are a direct cause for (and not only a result of) the emergence and the growth of intron code. The influence of non-neutral variations has been found to be considerably smaller. Neutral variations turned out to be beneficial by solving two classification problems more successfully.",
-
notes = "EuroGP'2003 held in conjunction with EvoWorkshops
2003
Section 2.3 PerlGP 'In PerlGP \cite{maccallum03}, evolved code is expanded from a tree-based genotype into a string before being evaluated with Perl's eval() function. The trees of each individual are built (and later, mutated) according to a grammar and are strongly typed. In this application, we want the evolved code to look like the example given in Figure 3; that is to say, the solution should be some arithmetic expression containing constants and RE matches against a protein sequence. The matches() function feeds the number of separate RE matches into the arithmetic expression. If the result of the expression for a given sequence is greater than zero, it is predicted/classified as nuclear, otherwise it is non-nuclear.'
",
