Multiobjective Parsimony Enforcement for Superior
Generalisation Performance
Proceedings of the 2004 IEEE Congress on Evolutionary
Computation, page 83--89. Portland, Oregon, IEEE Press, (20-23 June 2004)Abstract
Program Bloat - the phenomenon of ever-increasing
program size during a GP run - is a recognised and
widespread problem. Traditional techniques to combat
program bloat are program size limitations or parsimony
pressure (penalty functions). These techniques suffer
from a number of problems, in particular their reliance
on parameters whose optimal values it is difficult to a
priori determine. In this paper we introduce POPE-GP, a
system that makes use of the NSGA-II multiobjective
evolutionary algorithm as an alternative,
parameter-free technique for eliminating program bloat.
We test it on a classification problem and find that
while vastly reducing program size, it does improve
generalisation performance.
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