abstract = "In genetic programming, the reproductive operators of
crossover and mutation both require the selection of
nodes from the reproducing individuals. Both unbiased
random selection and Koza 90/10 mechanisms remain
popular, despite their arbitrary natures and a lack of
evidence for their effectiveness. It is generally
considered problematic to select from all nodes with a
uniform distribution, since this causes terminal nodes
to be selected most of the time. This can limit the
complexity of program fragments that can be exchanged
in crossover, and it may also lead to code bloat when
leaf nodes are replaced with larger new subtrees during
mutation. We present a new node selection method that
selects nodes based on a tournament, from which the
largest participating subtree is selected. We show this
method of size-based tournaments improves performance
on three standard test problems with no increases in
code bloat as compared to unbiased and Koza 90/10
selection methods.",
notes = "Also known as \cite{2002095} Distributed on CD-ROM at
GECCO-2011.