Enhancing the performance of GP using an ancestry-based mate selection scheme

Authors:
Rodney Fry;Andy Tyrrell
Affiliations:
Department of Electronics, University of York, UK;Department of Electronics, University of York, UK
Venue:
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Year:
2003

Citing 2
Cited 1

Genetic programming: on the programming of computers by means of natural selection

Genetic programming: on the programming of computers by means of natural selection
Enhancing GA Performance through Crossover Prohibitions Based on Ancestry

Proceedings of the 6th International Conference on Genetic Algorithms

A survey and taxonomy of performance improvement of canonical genetic programming

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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.