Genetic Programming: Introduction, Applications, Theory and Open Issues

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Leonardo Vanneschi and Riccardo Poli",
  title =        "Genetic Programming: Introduction, Applications,
                 Theory and Open Issues",
  booktitle =    "Handbook of Natural Computing",
  publisher =    "Springer",
  year =         "2012",
  editor =       "Grzegorz Rozenberg and Thomas Baeck and Joost N. Kok",
  volume =       "2",
  chapter =      "24",
  pages =        "709--739",
  month =        "19 " # aug,
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-540-92909-3",
  URL =          "",
  URL =          "",
  DOI =          "doi:10.1007/978-3-540-92910-9_24",
  abstract =     "Genetic programming (GP) is an evolutionary approach
                 that extends genetic algorithms to allow the
                 exploration of the space of computer programs. Like
                 other evolutionary algorithms, GP works by defining a
                 goal in the form of a quality criterion (or fitness)
                 and then using this criterion to evolve a set (or
                 population) of candidate solutions (individuals) by
                 mimicking the basic principles of Darwinian evolution.
                 GP breeds the solutions to problems using an iterative
                 process involving the probabilistic selection of the
                 fittest solutions and their variation by means of a set
                 of genetic operators, usually crossover and mutation.
                 GP has been successfully applied to a number of
                 challenging real-world problem domains. Its operations
                 and behaviour are now reasonably well understood thanks
                 to a variety of powerful theoretical results. In this
                 chapter, the main definitions and features of GP are
                 introduced and its typical operations are described.
                 Some of its applications are then surveyed. Some
                 important theoretical results in this field, including
                 some very recent ones, are reviewed and some of the
                 most challenging open issues and directions for future
                 research are discussed.",
  notes =        "The Mechanics of Tree-Based GP, Examples of Real-World
                 Applications of GP, GP Theory, Open Issues",
  size =         "31 pages",

Genetic Programming entries for Leonardo Vanneschi Riccardo Poli