Bloat control in genetic programming by evaluating contribution of nodes

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

@InProceedings{DBLP:conf/gecco/SongCZ09,
  author =       "Andy Song and Dunhai Chen and Mengjie Zhang",
  title =        "Bloat control in genetic programming by evaluating
                 contribution of nodes",
  booktitle =    "GECCO '09: Proceedings of the 11th Annual conference
                 on Genetic and evolutionary computation",
  year =         "2009",
  editor =       "Guenther Raidl and Franz Rothlauf and 
                 Giovanni Squillero and Rolf Drechsler and Thomas Stuetzle and 
                 Mauro Birattari and Clare Bates Congdon and 
                 Martin Middendorf and Christian Blum and Carlos Cotta and 
                 Peter Bosman and Joern Grahl and Joshua Knowles and 
                 David Corne and Hans-Georg Beyer and Ken Stanley and 
                 Julian F. Miller and Jano {van Hemert} and 
                 Tom Lenaerts and Marc Ebner and Jaume Bacardit and 
                 Michael O'Neill and Massimiliano {Di Penta} and Benjamin Doerr and 
                 Thomas Jansen and Riccardo Poli and Enrique Alba",
  pages =        "1893--1894",
  address =      "Montreal",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  month =        "8-12 " # jul,
  organisation = "SigEvo",
  keywords =     "genetic algorithms, genetic programming, Poster",
  isbn13 =       "978-1-60558-325-9",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  DOI =          "doi:10.1145/1569901.1570221",
  abstract =     "Unnecessary growth in program size is known as bloat
                 problem in Genetic Programming. There are a large
                 number of studies addressing this problem. In this
                 paper, we propose an effective bloat control mechanism
                 which is based on examining the contribution of each
                 function node in the selected programs. Nodes without
                 contribution will be removed before generating
                 offspring. The results show that the method can
                 significantly reduce program size without compromising
                 fitness. Furthermore it speeds up evolution processes
                 because of the saving in evaluation costs.",
  notes =        "GECCO-2009 A joint meeting of the eighteenth
                 international conference on genetic algorithms
                 (ICGA-2009) and the fourteenth annual genetic
                 programming conference (GP-2009).

                 ACM Order Number 910092.",
}

Genetic Programming entries for Andy Song Dunhai Chen Mengjie Zhang

Citations