Clustering Based Niching for Genetic Programming in the R Environment

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

@InProceedings{Flas10f,
  author =       "Oliver Flasch and Thomas Bartz-beielstein and 
                 Patrick Koch and Wolfgang Konen",
  title =        "Clustering Based Niching for Genetic Programming in
                 the R Environment",
  booktitle =    "Proceedings 20. Workshop Computational Intelligence",
  year =         "2010",
  editor =       "Frank Hoffmann and Eyke Huellermeier",
  pages =        "33--46",
  publisher =    "Universitaetsverlag Karlsruhe",
  keywords =     "genetic algorithms, genetic programming",
  pubstate =     "published",
  annote =       "Fakult{\"a}t F{\"u}r Informatik Und
                 Ingenieurwissenschaften; The Pennsylvania State
                 University CiteSeerX Archives",
  bibsource =    "OAI-PMH server at citeseerx.ist.psu.edu",
  language =     "en",
  oai =          "oai:CiteSeerX.psu:10.1.1.301.5035",
  rights =       "Metadata may be used without restrictions as long as
                 the oai identifier remains attached to it.",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.301.5035",
  URL =          "http://www.gm.fh-koeln.de/~bartz/Papers.d/Flas10f.pdf",
  URL =          "http://lwibs01.gm.fh-koeln.de/blogs/konen/publications-wolfgang-konen/?tgid=20&yr&type&auth",
  abstract =     "In this paper, we give a short introduction into RGP,
                 a new genetic programming (GP) system based on the
                 statistical package R. The system implements classical
                 untyped tree-based genetic programming as well as more
                 advanced variants including, for example, strongly
                 typed genetic programming and Pareto genetic
                 programming. The main part of this paper is concerned
                 with the problem of premature convergence of GP
                 populations, accompanied by a loss of genetic
                 diversity, resulting in poor effectiveness of the
                 search. We propose a clustering based niching approach
                 to mitigate this problem. The results of preliminary
                 experiments confirm that clustering based niching is
                 effective in preserving genetic diversity in GP
                 populations.",
}

Genetic Programming entries for Oliver Flasch Thomas Bartz-Beielstein Patrick Koch Wolfgang Konen

Citations