An Empirical Study on the Parametrization of Cartesian Genetic Programming

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

  author =       "Paul Kaufmann and Roman Kalkreuth",
  title =        "An Empirical Study on the Parametrization of Cartesian
                 Genetic Programming",
  booktitle =    "Proceedings of the Genetic and Evolutionary
                 Computation Conference Companion",
  series =       "GECCO '17",
  year =         "2017",
  isbn13 =       "978-1-4503-4939-0",
  address =      "Berlin, Germany",
  pages =        "231--232",
  size =         "2 pages",
  URL =          "",
  DOI =          "doi:10.1145/3067695.3075980",
  acmid =        "3075980",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  month =        "15-19 " # jul,
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming",
  abstract =     "Since its introduction two decades ago, the way
                 researchers parametrised and optimized Cartesian
                 Genetic Programming (CGP) remained almost unchanged. In
                 this work we investigate non-standard parametrisations
                 and optimization algorithms for CGP. We show that the
                 conventional way of using CGP, i.e. configuring it as a
                 single line optimized by an (1+4) Evolutionary
                 Strategies-style search scheme, is a very good choice
                 but that rectangular CGP geometries and more elaborate
                 metaheuristics, such as Simulated Annealing, can lead
                 to faster convergence rates.",
  notes =        "Also known as \cite{Kaufmann:2017:ESP:3067695.3075980}
                 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 Paul Kaufmann Roman Kalkreuth