Quadratic Bloat in Genetic Programming
Proceedings of the Genetic and Evolutionary
Computation Conference (GECCO-2000), page 451--458. Las Vegas, Nevada, USA, Morgan Kaufmann, (10-12 July 2000)Abstract
In earlier work we predicted program size would grow
in the limit at a quadratic rate and up to fifty
generations we measured bloat
O(generations**(1.2-1.5)). On two simple benchmarks we
test the prediction of bloat O(generations**2.0) up to
generation 600. In continuous problems the limit of
quadratic growth is reached but convergence in the
discrete case limits growth in size. Measurements
indicate subtree crossover ceases to be disruptive with
large programs (1,000,000) and the population
effectively converges (even though variety is near
unity). Depending upon implementation, we predict run
time O(number of generations**(2.0-3.0)) and memory
O(number of generations**(1.0-2.0)).
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