The influence of population size in geometric semantic GP

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Castelli:2017:SEC,
  author =       "Mauro Castelli and Luca Manzoni and Sara Silva and 
                 Leonardo Vanneschi and Ales Popovic",
  title =        "The influence of population size in geometric semantic
                 {GP}",
  journal =      "Swarm and Evolutionary Computation",
  volume =       "32",
  pages =        "110--120",
  year =         "2017",
  ISSN =         "2210-6502",
  DOI =          "doi:10.1016/j.swevo.2016.05.004",
  URL =          "http://www.sciencedirect.com/science/article/pii/S2210650216300256",
  abstract =     "In this work, we study the influence of the population
                 size on the learning ability of Geometric Semantic
                 Genetic Programming for the task of symbolic
                 regression. A large set of experiments, considering
                 different population size values on different
                 regression problems, has been performed. Results show
                 that, on real-life problems, having small populations
                 results in a better training fitness with respect to
                 the use of large populations after the same number of
                 fitness evaluations. However, performance on the test
                 instances varies among the different problems: in
                 datasets with a high number of features, models
                 obtained with large populations present a better
                 performance on unseen data, while in datasets
                 characterized by a relative small number of variables a
                 better generalization ability is achieved by using
                 small population size values. When synthetic problems
                 are taken into account, large population size values
                 represent the best option for achieving good quality
                 solutions on both training and test instances.",
  keywords =     "genetic algorithms, genetic programming, Semantics,
                 Population size",
}

Genetic Programming entries for Mauro Castelli Luca Manzoni Sara Silva Leonardo Vanneschi Ales Popovic

Citations