How functional dependency adapts to salience hierarchy in the GAuGE system

Authors:
Miguel Nicolau;Conor Ryan
Affiliations:
Department of Computer Science And Information Systems, University of Limerick, Ireland;Department of Computer Science And Information Systems, University of Limerick, Ireland
Venue:
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
Year:
2003

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Abstract

GAuGE is a position independent genetic algorithm that suffers from neither under nor over-specification, and uses a genotype to phenotype mapping process. By specifying both the position and the value of each gene, it has the potential to group important data together in the genotype string, to prevent it from being broken up and disrupted during the evolution process. To test this ability, GAuGE was applied to a set of problems with exponentially scaled salience. The results obtained demonstrate that GAuGE is indeed moving the more salient genes to the start of the genotype strings, creating robust individuals that are built in a progressive fashion from the left to the right side of the genotype.