Seeding GP Populations

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{langdon:2000:seed,
  author =       "W. B. Langdon and J. P. Nordin",
  title =        "Seeding {GP} Populations",
  booktitle =    "Genetic Programming, Proceedings of EuroGP'2000",
  year =         "2000",
  editor =       "Riccardo Poli and Wolfgang Banzhaf and 
                 William B. Langdon and Julian F. Miller and Peter Nordin and 
                 Terence C. Fogarty",
  volume =       "1802",
  series =       "LNCS",
  pages =        "304--315",
  address =      "Edinburgh",
  publisher_address = "Berlin",
  month =        "15-16 " # apr,
  organisation = "EvoNet",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming, Pareto
                 multi-objective fitness: Poster",
  ISBN =         "3-540-67339-3",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/WBL_eurogp2000_seed.pdf",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/WBL_eurogp2000_seed.ps.gz",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=1802&spage=304",
  DOI =          "doi:10.1007/978-3-540-46239-2_23",
  size =         "12 pages",
  abstract =     "We show GP populations can evolve from perfect
                 programs which match the training material under the
                 influence of a Pareto multi-objective fitness and
                 program size selection scheme to generalise. The
                 technique is demonstrated upon programmatic image
                 compression, two machine learning benchmark problems
                 (Pima Diabetes and Wisconsin Breast Cancer) and a
                 consumer profiling task (Benelearn99).",
  notes =        "EuroGP'2000, part of \cite{poli:2000:GP}",
}

Genetic Programming entries for William B Langdon Peter Nordin

Citations