abstract = "Research has shown that beyond a certain minimum
program length the distributions of program
functionality and fitness converge to a limit. Before
that limit, however, there may be program-length
classes with a higher or lower average fitness than
that achieved beyond the limit. Ideally, therefore, GP
search should be limited to program lengths that are
within the limit and that can achieve optimum fitness.
This has the dual benefits of providing the
simplest/smallest solutions and preventing GP bloat
thus shortening run times. Here we introduce a novel
and simple technique, which we call Operator
Equalisation, to control how GP will sample certain
length classes. This allows us to finely and freely
bias the search towards shorter or longer programs and
also to search specific length classes during a GP run.
This gives the user total control on the program length
distribution, thereby completely freeing GP from bloat.
Results show that we can automatically identify
potentially optimal solution length classes quickly
using small samples and that, for particular classes of
problems, simple length biases can significantly
improve the best fitness found during a GP run.",
notes = "Also known as \cite{conf/eurogp/DignumP08}