PonyGE2: Grammatical Evolution in Python

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

@InProceedings{Fenton:2017:GECCOa,
  author =       "Michael Fenton and James McDermott and David Fagan and 
                 Stefan Forstenlechner and Erik Hemberg and 
                 Michael O'Neill",
  title =        "{PonyGE2}: Grammatical Evolution in Python",
  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 =        "1194--1201",
  size =         "8 pages",
  URL =          "http://doi.acm.org/10.1145/3067695.3082469",
  DOI =          "doi:10.1145/3067695.3082469",
  acmid =        "3082469",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution",
  month =        "15-19 " # jul,
  abstract =     "Grammatical Evolution (GE) is a population-based
                 evolutionary algorithm, where a formal grammar is used
                 in the genotype to phenotype mapping process. PonyGE2
                 is an open source implementation of GE in Python,
                 developed at UCD's Natural Computing Research and
                 Applications group. It is intended as an advertisement
                 and a starting-point for those new to GE, a reference
                 for students and researchers, a rapid-prototyping
                 medium for our own experiments, and a Python workout.
                 As well as providing the characteristic genotype to
                 phenotype mapping of GE, a search algorithm engine is
                 also provided. A number of sample problems and
                 tutorials on how to use and adapt PonyGE2 have been
                 developed.",
  notes =        "Also known as \cite{Fenton:2017:PGE:3067695.3082469}
                 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 Michael Fenton James McDermott David Fagan Stefan Forstenlechner Erik Hemberg Michael O'Neill

Citations