Self-adaptation of Genetic Operators Through Genetic Programming Techniques

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Andres Felipe Cruz-Salinas and Jonatan Gomez Perdomo",
  title =        "Self-adaptation of Genetic Operators Through Genetic
                 Programming Techniques",
  booktitle =    "Proceedings of the Genetic and Evolutionary
                 Computation Conference",
  series =       "GECCO '17",
  year =         "2017",
  isbn13 =       "978-1-4503-4920-8",
  address =      "Berlin, Germany",
  pages =        "913--920",
  size =         "8 pages",
  URL =          "",
  DOI =          "doi:10.1145/3071178.3071214",
  acmid =        "3071214",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  keywords =     "genetic algorithms, genetic programming, evolutionary
                 algorithms, real optimization, self-adaptation,
                 self-adapted operators",
  month =        "15-19 " # jul,
  abstract =     "Here we propose an evolutionary algorithm that self
                 modifies its operators at the same time that candidate
                 solutions are evolved. This tackles convergence and
                 lack of diversity issues, leading to better solutions.
                 Operators are represented as trees and are evolved
                 using genetic programming (GP) techniques. The proposed
                 approach is tested with real benchmark functions and an
                 analysis of operator evolution is provided.",
  notes =        "Also known as
                 \cite{Cruz-Salinas:2017:SGO:3071178.3071214} GECCO-2017
                 A Recombination of the 26th International Conference on
                 Genetic Algorithms (ICGA-2017) and the 22nd Annual
                 Genetic Programming Conference (GP-2017)",

Genetic Programming entries for Andres Felipe Cruz-Salinas Jonatan Gomez Perdomo