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Enhancing the Performance of GP Using an Ancestry-Based Mate Selection Scheme
Rodney Fry and Andy Tyrrell
Department of Electronics
University of York, UK
{rjlf101,amt}@ohm.york.ac.uk
Abstract. The performance of genetic programming relies mostly on population-contained variation. If the population diversity is low then there will be a greater chance of the algorithm being unable to find the global optimum. We present a new method of approximating the genetic similarity between two individuals using ancestry information. We define a new diversity-preserving selection scheme, based on standard tournament selection, which encourages genetically dissimilar individuals to undergo genetic operation. The new method is illustrated by assessing its performance in a well-known problem domain: algebraic symbolic regression.
LNCS 2724, p. 1804 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2003