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Enhancing the Performance of GP Using an Ancestry-Based Mate Selection Scheme

, и . Genetic and Evolutionary Computation -- GECCO-2003, том 2724 из LNCS, стр. 1804--1805. Chicago, Springer-Verlag, (12-16 July 2003)

Аннотация

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.

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