Examining the landscape of semantic similarity based mutation

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@InProceedings{Nguyen:2011:GECCO,
  author =       "Nguyen Quang Uy and Xuan Hoai Nguyen and 
                 Michael O'Neill",
  title =        "Examining the landscape of semantic similarity based
                 mutation",
  booktitle =    "GECCO '11: Proceedings of the 13th annual conference
                 on Genetic and evolutionary computation",
  year =         "2011",
  editor =       "Natalio Krasnogor and Pier Luca Lanzi and 
                 Andries Engelbrecht and David Pelta and Carlos Gershenson and 
                 Giovanni Squillero and Alex Freitas and 
                 Marylyn Ritchie and Mike Preuss and Christian Gagne and 
                 Yew Soon Ong and Guenther Raidl and Marcus Gallager and 
                 Jose Lozano and Carlos Coello-Coello and Dario Landa Silva and 
                 Nikolaus Hansen and Silja Meyer-Nieberg and 
                 Jim Smith and Gus Eiben and Ester Bernado-Mansilla and 
                 Will Browne and Lee Spector and Tina Yu and Jeff Clune and 
                 Greg Hornby and Man-Leung Wong and Pierre Collet and 
                 Steve Gustafson and Jean-Paul Watson and 
                 Moshe Sipper and Simon Poulding and Gabriela Ochoa and 
                 Marc Schoenauer and Carsten Witt and Anne Auger",
  isbn13 =       "978-1-4503-0557-0",
  pages =        "1363--1370",
  keywords =     "genetic algorithms, genetic programming",
  month =        "12-16 " # jul,
  organisation = "SIGEVO",
  address =      "Dublin, Ireland",
  doi =          "doi:10.1145/2001576.2001760",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "This paper examines how the semantic locality of a
                 search operator affects the fitness landscape of
                 Genetic Programming (GP). We compare the fitness
                 landscapes of GP search when standard subtree mutation
                 and arecently proposed semantic-based mutation,
                 Semantic Similarity-based Mutation (SSM), are used. The
                 comparison is based on two well-studied fitness
                 landscape measures, namely, the autocorrelation
                 function and information content. The experiments were
                 conducted on a family of symbolic regression problems
                 with increasing degrees of difficulty. The results show
                 that SSM helps to significantly smooth out the fitness
                 landscape of GP compared to standard subtree mutation.
                 This gives an explanation for the better performance of
                 SSM over standard subtree mutation operator.",
  notes =        "Nguyen Quang Uy???? TAG alpha-beta grammar tree

                 Also known as \cite{2001760} GECCO-2011 A joint meeting
                 of the twentieth international conference on genetic
                 algorithms (ICGA-2011) and the sixteenth annual genetic
                 programming conference (GP-2011)",
}

Genetic Programming entries for Quang Uy Nguyen Nguyen Xuan Hoai Michael O'Neill