Towards effective semantic operators for program synthesis in genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Stefan Forstenlechner and David Fagan and 
                 Miguel Nicolau and Michael O'Neill",
  title =        "Towards effective semantic operators for program
                 synthesis in genetic programming",
  booktitle =    "GECCO '18: Proceedings of the Genetic and Evolutionary
                 Computation Conference",
  year =         "2018",
  editor =       "Hernan Aguirre and Keiki Takadama and 
                 Hisashi Handa and Arnaud Liefooghe and Tomohiro Yoshikawa and 
                 Andrew M. Sutton and Satoshi Ono and Francisco Chicano and 
                 Shinichi Shirakawa and Zdenek Vasicek and 
                 Roderich Gross and Andries Engelbrecht and Emma Hart and 
                 Sebastian Risi and Ekart Aniko and Julian Togelius and 
                 Sebastien Verel and Christian Blum and Will Browne and 
                 Yusuke Nojima and Tea Tusar and Qingfu Zhang and 
                 Nikolaus Hansen and Jose Antonio Lozano and 
                 Dirk Thierens and Tian-Li Yu and Juergen Branke and 
                 Yaochu Jin and Sara Silva and Hitoshi Iba and 
                 Anna I Esparcia-Alcazar and Thomas Bartz-Beielstein and 
                 Federica Sarro and Giuliano Antoniol and Anne Auger and 
                 Per Kristian Lehre",
  isbn13 =       "978-1-4503-5618-3",
  pages =        "1119--1126",
  address =      "Kyoto, Japan",
  DOI =          "doi:10.1145/3205455.3205592",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  month =        "15-19 " # jul,
  organisation = "SIGEVO",
  keywords =     "genetic algorithms, genetic programming",
  abstract =     "the use of semantic information in genetic programming
                 operators has shown major improvements in recent years,
                 especially in the regression and boolean domain. As
                 semantic information is domain specific, using it in
                 other areas poses certain problems. Semantic operators
                 require being adapted for the problem domain they are
                 applied to. An attempt to create a semantic crossover
                 for program synthesis has been made with rather limited
                 success, but the results have provided insights about
                 using semantics in program synthesis. Based on this
                 initial attempt, this paper presents an improved
                 version of semantic operators for program synthesis,
                 which contains a small but significant change to the
                 overall functionality, as well as a novel measure for
                 the comparison of the semantics of subtrees. The
                 results show that the improved semantic crossover is
                 superior to the previous semantic operator in the
                 program synthesis domain.",
  notes =        "Checksum, Compare String Lengths, Double Letters,
                 Grade, Mirror Image, Small Or Large, Sum of Squares and
                 Vector Average.

                 Also known as \cite{3205592} GECCO-2018 A Recombination
                 of the 27th International Conference on Genetic
                 Algorithms (ICGA-2018) and the 23rd Annual Genetic
                 Programming Conference (GP-2018)",

Genetic Programming entries for Stefan Forstenlechner David Fagan Miguel Nicolau Michael O'Neill