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    Associate Professor

    Computer Science, Universidad Autonoma de Madrid, Madrid

    An Empirical Study on the Accuracy of Computational Effort in Genetic Programming

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    Some commonly used performance measures in Genetic Programming are those defined by John Koza in his first book. These measures, mainly computational effort and number of individuals to be processed, estimate the performance of the algorithm as well as the difficulty of a problem. Although Koza's performance measures have been widely used in the literature, their behaviour is not well known. In this paper we try to study the accuracy of these measures and advance in the understanding of the factors that influence them. In order to achieve this goal, we report an empirical study that attempts to systematically measure the effects of two variability sources in the estimation of the number of individuals to be processed and the computational effort. The results obtained in those experiments suggests that these measures, in common experimental setups, and under certain circumstances, might have a high relative error.

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    Description

    Title : An Empirical Study on the Accuracy of Computational Effort in Genetic Programming
    Author(s) : David F Barrero, Maria R-Moreno, Bonifacio Castano, David Camacho
    Abstract : Some commonly used performance measures in Genetic Programming are those defined by John Koza in his first book. These measures, mainly computational effort and number of individuals to be processed, estimate the performance of the algorithm as well as the difficulty of a problem. Although Koza's performance measures have been widely used in the literature, their behaviour is not well known. In this paper we try to study the accuracy of these measures and advance in the understanding of the factors that influence them. In order to achieve this goal, we report an empirical study that attempts to systematically measure the effects of two variability sources in the estimation of the number of individuals to be processed and the computational effort. The results obtained in those experiments suggests that these measures, in common experimental setups, and under certain circumstances, might have a high relative error.
    Subject : unspecified
    Area : Other
    Language : English
    Year : 2011

    Affiliations Computer Science, Universidad Autonoma de Madrid, Madrid
    Editors : Alice E Smith
    Journal : Proceedings of the 2011 IEEE Congress on Evolutionary Computatio
    Publisher : IEEE Press
    Pages : 1169-1176
    Url : http://api.mendeley.com/research/empirical-study-accuracy-computational-effort-genetic-programming/

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    David's Peer Evaluation activity

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