DEAP: a Python framework for evolutionary algorithms

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

  author =       "Francois-Michel {De Rainville} and 
                 Felix-Antoine Fortin and Marc-Andre Gardner and Marc Parizeau and 
                 Christian Gagne",
  title =        "DEAP: a Python framework for evolutionary algorithms",
  booktitle =    "GECCO 2012 Evolutionary Computation Software Systems
  year =         "2012",
  editor =       "Stefan Wagner and Michael Affenzeller",
  pages =        "85--92",
  month =        "7-11 " # jul,
  organisation = "SIGEVO",
  address =      "Philadelphia, Pennsylvania, USA",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-1-4503-1178-6",
  DOI =          "doi:10.1145/2330784.2330799",
  abstract =     "DEAP (Distributed Evolutionary Algorithms in Python)
                 is a novel evolutionary computation framework for rapid
                 prototyping and testing of ideas. Its design departs
                 from most other existing frameworks in that it seeks to
                 make algorithms explicit and data structures
                 transparent, as opposed to the more common black box
                 type of frameworks. It also incorporates easy
                 parallelism where users need not concern themselves
                 with gory implementation details like synchronisation
                 and load balancing, only functional decomposition.
                 Several examples illustrate the multiple properties of
  notes =        "Also known as \cite{2330799} Distributed at

                 ACM Order Number 910122.",

Genetic Programming entries for Francois-Michel De Rainville Felix-Antoine Fortin Marc-Andre Gardner Marc Parizeau Christian Gagne