Abstract
Size fair and homologous crossover genetic operators
for tree based genetic programming are described and
tested. Both produce 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 versus 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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