Developments in Cartesian Genetic Programming: self-modifying CGP

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Harding:2010:GPEM,
  author =       "Simon Harding and Julian F. Miller and 
                 Wolfgang Banzhaf",
  title =        "Developments in Cartesian Genetic Programming:
                 self-modifying CGP",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2010",
  volume =       "11",
  number =       "3/4",
  pages =        "397--439",
  month =        sep,
  note =         "Tenth Anniversary Issue: Progress in Genetic
                 Programming and Evolvable Machines",
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 Genetic Programming, Developmental systems",
  ISSN =         "1389-2576",
  DOI =          "doi:10.1007/s10710-010-9114-1",
  URL =          "http://results.ref.ac.uk/Submissions/Output/3354577",
  size =         "43 pages",
  abstract =     "Self-modifying Cartesian Genetic Programming (SMCGP)
                 is a general purpose, graph-based, developmental form
                 of Genetic Programming founded on Cartesian Genetic
                 Programming. In addition to the usual computational
                 functions, it includes functions that can modify the
                 program encoded in the genotype. This means that
                 programs can be iterated to produce an infinite
                 sequence of programs (phenotypes) from a single evolved
                 genotype. It also allows programs to acquire more
                 inputs and produce more outputs during this iteration.
                 We discuss how SMCGP can be used and the results
                 obtained in several different problem domains,
                 including digital circuits, generation of patterns and
                 sequences, and mathematical problems. We find that
                 SMCGP can efficiently solve all the problems studied.
                 In addition, we prove mathematically that evolved
                 programs can provide general solutions to a number of
                 problems: n-input even-parity, n-input adder, and
                 sequence approximation to pi",
  uk_research_excellence_2014 = "The paper advances evolutionary
                 computation. Published in this special issue of the
                 journal to mark its tenth anniversary and calling for
                 far-reaching and foundational work. The result of
                 collaborations with Memorial University of
                 Newfoundland, Canada the paper introduces the concept
                 of self-modification in Genetic Programming (GP). For
                 the first time this allows GP to be applied to multiple
                 instances of problems, and shows that general,
                 mathematically provable solutions to classes of
                 problems can be evolved.",
}

Genetic Programming entries for Simon Harding Julian F Miller Wolfgang Banzhaf

Citations