Abstract
Bloat is a common and well studied problem in genetic programming. Size and depth limits are often used to combat bloat, but to date there has been little detailed exploration of the effects and biases of such limits. In this paper we present empirical analysis of the effects of size and depth limits on binary tree genetic programs. We find that size limits control population average size in much the same way as depth limits do. Our data suggests, however that size limits provide finer and more reliable control than depth limits, which has less of an impact upon tree shapes.
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Crane, E.F., McPhee, N.F. (2006). The Effects of Size and Depth Limits on Tree Based Genetic Programming. In: Yu, T., Riolo, R., Worzel, B. (eds) Genetic Programming Theory and Practice III. Genetic Programming, vol 9. Springer, Boston, MA. https://doi.org/10.1007/0-387-28111-8_15
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DOI: https://doi.org/10.1007/0-387-28111-8_15
Publisher Name: Springer, Boston, MA
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