Abstraction-Based Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Franck J. L. Binard",
  title =        "Abstraction-Based Genetic Programming",
  school =       "Ottawa-Carleton Institute for Computer Science, School
                 of Information Technology and Engineering, Faculty of
                 Engineering, University of Ottawa",
  year =         "2009",
  address =      "Ottawa, Canada",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.site.uottawa.ca/~fbinard/Articles/FranckBinardPhDThesisLastVersion.pdf",
  size =         "178 pages",
  abstract =     "This thesis describes a novel method for representing
                 and automatically generating computer programs in an
                 evolutionary computation context. Abstraction-Based
                 Genetic Programming (ABGP) is a typed Genetic
                 Programming representation system that uses System F,
                 an expressive lambda-calculus, to represent the
                 computational components from which the evolved
                 programs are assembled. ABGP is based on the
                 manipulation of closed, independent modules expressing
                 computations with effects that have the ability to
                 affect the whole genotype . These modules are plugged
                 into other modules according to precisely defined rules
                 to form complete computer programs. The use of System F
                 allows the straightforward representation and use of
                 many typical computational structures and behaviours
                 (such as iteration, recursion, lists and trees) in
                 modular form. This is done without introducing
                 additional external symbols in the set of predefined
                 functions and terminals of the system. In fact,
                 programming structures typically included in GP
                 terminal sets, such as if then else, may be removed and
                 represented as abstractions in ABGP for the same
                 problems. ABGP also provides a search space
                 partitioning system based on the structure of the
                 genotypes, similar to the species partitioning system
                 of living organisms and derived from the Curry-Howard
                 isomorphism. This thesis also presents the results
                 obtained by applying this method to a set of

Genetic Programming entries for Franck J L Binard