Evolution of iteration in genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4333

  author =       "John R. Koza and David Andre",
  title =        "Evolution of iteration in genetic programming",
  booktitle =    "Evolutionary Programming V: Proceedings of the Fifth
                 Annual Conference on Evolutionary Programming",
  year =         "1996",
  editor =       "Lawrence J. Fogel and Peter J. Angeline and 
                 Thomas Baeck",
  address =      "San Diego",
  publisher_address = "Cambridge, MA, USA",
  month =        feb # " 29-" # mar # " 3",
  publisher =    "MIT Press",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-262-06190-2",
  URL =          "http://www.genetic-programming.com/jkpdf/ep1996.pdf",
  URL =          "http://citeseer.ist.psu.edu/153818.html",
  abstract =     "The solution to many problems requires, or is
                 facilitated by, the use of iteration. Moreover, because
                 iterative steps are repeatedly executed, they must have
                 some degree of generality. An automatic programming
                 system should require that the user make as few
                 problem-specific decisions as possible concerning the
                 size, shape, and character of the ultimate solution to
                 the problem. Work first presented at the Fourth Annual
                 Conference on Evolutionary Programming in 1995 (EP-95)
                 demonstrated that six then-new architecture-altering
                 operations made it possible to automate the decision
                 about the architecture of an overall program
                 dynamically during a run of genetic programming. The
                 question arises as to whether it is also possible to
                 automate the decision about whether to employ
                 iteration, how much iteration to employ, and the
                 particular sequence of iterative steps. This paper
                 introduces the new operation of restricted iteration
                 creation that automatically creates a restricted
                 iteration-performing branch out of a portion of an
                 existing computer program during a run a genetic
                 programming. Genetic programming with the new operation
                 is then used (in conjunction with the other
                 architecture-altering operations first presented at
                 EP-95) to evolve a computer program to solve a
                 non-trivial problem",
  notes =        "EP-96


Genetic Programming entries for John Koza David Andre