Two Ways of Discovering the Size and Shape of a Computer Program to Solve a Problem

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

  author =       "John R. Koza",
  title =        "Two Ways of Discovering the Size and Shape of a
                 Computer Program to Solve a Problem",
  booktitle =    "Genetic Algorithms: Proceedings of the Sixth
                 International Conference (ICGA95)",
  year =         "1995",
  editor =       "Larry J. Eshelman",
  pages =        "287--294",
  address =      "Pittsburgh, PA, USA",
  publisher_address = "San Francisco, CA, USA",
  month =        "15-19 " # jul,
  publisher =    "Morgan Kaufmann",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "1-55860-370-0",
  URL =          "",
  abstract =     "The requirement that the user predetermine the size
                 and shape of the ultimate solution to a problem has
                 been a bane of automated machine learning from the
                 earliest times. This paper compares two techniques for
                 automatically discovering, during a run of genetic
                 programming, the architecture of a multi-part computer
                 program while concurrently solving the problem. In the
                 first technique, called evolutionary selection, the
                 initial random population is architecturally diverse
                 and there is a competition during the run among the
                 various architectures while they are trying to solve
                 the problem. The second technique, called evolution of
                 architecture, employs six new architecture-altering
                 operations that provide a way to evolve the
                 architecture of a multi-part program in the sense of
                 actually changing the architecture of the program
                 dynamically during the run. The new
                 architecture-altering operations are motivated by the
                 naturally occurring operation of gene duplication, as
                 described in Susumu Ohno's provocative book Evolution
                 by Means of Gene Duplication.",

Genetic Programming entries for John Koza