Genetic C Programming with Probabilistic Evaluation

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

@InProceedings{Christmas:2015:GECCOcomp,
  author =       "Jacqueline Christmas",
  title =        "Genetic C Programming with Probabilistic Evaluation",
  booktitle =    "GECCO Companion '15: Proceedings of the Companion
                 Publication 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 =       "978-1-4503-3488-4",
  keywords =     "genetic algorithms, genetic programming: Poster",
  pages =        "1371--1372",
  month =        "11-15 " # jul,
  organisation = "SIGEVO",
  address =      "Madrid, Spain",
  URL =          "http://doi.acm.org/10.1145/2739482.2764642",
  DOI =          "doi:10.1145/2739482.2764642",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "We introduce the concept of probabilistic program
                 evaluation, whereby the order in which the statements
                 of a proposed program are executed, and whether
                 individual statements are executed at all, are
                 controlled by probability distributions associated with
                 each statement. The sufficient statistics of these
                 probability distributions are mutated as part of the GP
                 scheme. We demonstrate the method on the simple
                 problems of swapping two array elements and identifying
                 the maximum value in an array.",
  notes =        "EDA?

                 Also known as \cite{2764642} Distributed at
                 GECCO-2015.",
}

Genetic Programming entries for Jacqueline Christmas

Citations