Abstract
Size fair crossover genetic operator for tree based
genetic programming is described and tested. It
produces considerably reduced increases in program size
and no detrimental effect on GP performance. GP search
spaces are partitioned by the ridge in the number of
program v. their size and depth. A ramped uniform
random initialisation is described which straddles the
ridge. With subtree crossover trees increase about one
level per generation leading to sub-quadratic bloat in
length.
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