Statistical distribution of generation-to-success in GP: application to model accumulated success probability

Authors:
David F. Barrero;Bonifacio Castaño;María D. R-Moreno;David Camacho
Affiliations:
Universidad de Alcalá, Departamento de Automática, Alcalá de Henares, Madrid, Spain;Departamento de Matemáticas, Universidad de Alcalá;Universidad de Alcalá, Departamento de Automática, Alcalá de Henares, Madrid, Spain;Departamento de Informática, Universidad Autónoma de Madrid
Venue:
EuroGP'11 Proceedings of the 14th European conference on Genetic programming
Year:
2011

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Abstract

Many different metrics have been defined in Genetic Programming. Depending on the experiment requirements and objectives, a collection of measures are selected in order to achieve an understanding of the algorithm behaviour. One of the most common metrics is the accumulated success probability, which evaluates the probability of an algorithm to achieve a solution in a certain generation. We propose a model of accumulated success probability composed by two parts, a binomial distribution that models the total number of success, and a lognormal approximation to the generation-to-success, that models the variation of the success probability with the generation.