On the Bias of Syntactic Geometric Recombination in Genetic Programming and Grammatical Evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Thorhauer:2015:GECCO,
  author =       "Ann Thorhauer and Franz Rothlauf",
  title =        "On the Bias of Syntactic Geometric Recombination in
                 Genetic Programming and Grammatical Evolution",
  booktitle =    "GECCO '15: Proceedings of the 2015 Annual Conference
                 on Genetic and Evolutionary Computation",
  year =         "2015",
  editor =       "Sara Silva and Anna I Esparcia-Alcazar and 
                 Manuel Lopez-Ibanez and Sanaz Mostaghim and Jon Timmis and 
                 Christine Zarges and Luis Correia and Terence Soule and 
                 Mario Giacobini and Ryan Urbanowicz and 
                 Youhei Akimoto and Tobias Glasmachers and 
                 Francisco {Fernandez de Vega} and Amy Hoover and Pedro Larranaga and 
                 Marta Soto and Carlos Cotta and Francisco B. Pereira and 
                 Julia Handl and Jan Koutnik and Antonio Gaspar-Cunha and 
                 Heike Trautmann and Jean-Baptiste Mouret and 
                 Sebastian Risi and Ernesto Costa and Oliver Schuetze and 
                 Krzysztof Krawiec and Alberto Moraglio and 
                 Julian F. Miller and Pawel Widera and Stefano Cagnoni and 
                 JJ Merelo and Emma Hart and Leonardo Trujillo and 
                 Marouane Kessentini and Gabriela Ochoa and Francisco Chicano and 
                 Carola Doerr",
  isbn13 =       "978-1-4503-3472-3",
  pages =        "1103--1110",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution",
  month =        "11-15 " # jul,
  organisation = "SIGEVO",
  address =      "Madrid, Spain",
  URL =          "http://doi.acm.org/10.1145/2739480.2754726",
  DOI =          "doi:10.1145/2739480.2754726",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "For fixed-length binary representations as used in
                 genetic algorithms, standard recombination operators
                 (e.g.,~one-point crossover) are unbiased. Thus, the
                 application of recombination only reshuffles the
                 alleles and does not change the statistical properties
                 in the population. Using a geometric view on
                 recombination operators, most search operators for
                 fixed-length strings are geometric, which means that
                 the distances between offspring and their parents are
                 less than, or equal to, the distance between their
                 parents. In genetic programming (GP) and grammatical
                 evolution (GE), the situation is different since the
                 recombination operators are applied to variable-length
                 structures. Thus, most recombination operators for GE
                 and GP are not geometric.

                 This paper focuses on the bias of recombination in GE
                 and GP and studies whether the application of
                 recombination alone produces specific types of
                 solutions with a higher probability. We consider two
                 different types of recombination operators: standard
                 recombination and syntactic geometric recombination. In
                 our experiments, we performed random walks through the
                 binary tree search space and found that syntactic
                 geometric recombination operators are biased and
                 strongly reduce population diversity. In a performance
                 comparison, we found that syntactic geometric
                 recombination leads to large fitness improvements in
                 the first generations, but that fitness converges after
                 several generations and no further search is
                 possible.",
  notes =        "Also known as \cite{2754726} GECCO-2015 A joint
                 meeting of the twenty fourth international conference
                 on genetic algorithms (ICGA-2015) and the twentith
                 annual genetic programming conference (GP-2015)",
}

Genetic Programming entries for Ann Thorhauer Franz Rothlauf

Citations