Automatic Selection Pressure Control in Genetic Programming

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

@InProceedings{Xie:2006:ISDA,
  author =       "Huayang Xie and Mengjie Zhang and Peter Andreae",
  title =        "Automatic Selection Pressure Control in Genetic
                 Programming",
  booktitle =    "6th International Conference on Intelligent System
                 Design and Applications",
  year =         "2006",
  editor =       "Bo Yang and Yuehui Chen",
  pages =        "435--440",
  address =      "Jinan Nanjiao Hotel, Jinan, China",
  month =        oct # " 16-18",
  organisation = "EUSFLAT",
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-7695-2528-8",
  DOI =          "doi:10.1109/ISDA.2006.116",
  abstract =     "Selection pressure must be dynamically managed in
                 response to the changing evolutionary process in order
                 to improve the effectiveness and efficiency of Genetic
                 Programming (GP) systems using tournament selection.
                 Instead of changing the tournament size and/or the
                 population size via an arbitrary function to influence
                 the selection pressure, this paper focuses on designing
                 an automatic selection pressure control approach. In
                 our approach, populations are clustered based on a
                 dynamic program property. Then clusters become
                 tournament candidates. The selection pressure in the
                 tournament selection method is automatically changed
                 during evolution according to the dynamically changing
                 number of tournament candidates. Our approach is
                 compared with the standard GP system (with no selection
                 pressure control) on two problems with different kinds
                 of fitness distributions. The results show that the
                 automatic selection pressure control approach can
                 improve the effectiveness and efficiency of GP
                 systems.",
  notes =        "http://isda2006.ujn.edu.cn/",
}

Genetic Programming entries for Huayang Jason Xie Mengjie Zhang Peter Andreae

Citations