The genetic programming paradigm: Genetically breeding populations of computer programs to solve problems

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InCollection{Koza:1992:GPdgc,
  author =       "John R. Koza",
  title =        "The genetic programming paradigm: Genetically breeding
                 populations of computer programs to solve problems",
  booktitle =    "Dynamic, Genetic, and Chaotic Programming",
  publisher =    "John Wiley",
  year =         "1992",
  editor =       "Branko Soucek and the IRIS Group",
  pages =        "203--321",
  address =      "New York",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.genetic-programming.com/jkpdf/soucek1992.pdf",
  abstract =     "Many seemingly different problems in machine learning,
                 artificial intelligence, and symbolic processing can be
                 viewed as requiring the discovery of a computer program
                 that produces some desired output for particular
                 inputs. When viewed in this way, the process of solving
                 these problems becomes equivalent to searching a space
                 of possible computer programs for a highly fit
                 individual computer program. The recently developed
                 genetic programming paradigm described herein provides
                 a way to search the space of possible computer programs
                 for a highly fit individual computer program to solve
                 (or approximately solve) a surprising variety of
                 different problems from different fields. In the
                 genetic programming paradigm, populations of computer
                 programs are genetically bred using the Darwinian
                 principle of survival of the fittest and using a
                 genetic crossover (sexual recombination) operator
                 appropriate for genetically mating computer programs.
                 This chapter shows how to reformulate seemingly
                 different problems into a common form (i.e. a problem
                 requiring discovery of a computer program) and, then,
                 to show how the genetic programming paradigm can serve
                 as a single, unified approach for solving problems
                 formulated in this common way.",
  size =         "161 pages",
}

Genetic Programming entries for John Koza

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