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. © Springer-Verlag Berlin Heidelberg 2003.
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CITATION STYLE
Brameier, M., & Banzhaf, W. (2003). Neutral variations cause bloat in linear GP. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2610, 286–298. https://doi.org/10.1007/3-540-36599-0_26
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