General Schema Theory for Genetic Programming with Subtree-Swapping Crossover

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "Riccardo Poli",
  title =        "General Schema Theory for Genetic Programming with
                 Subtree-Swapping Crossover",
  booktitle =    "Genetic Programming, Proceedings of EuroGP'2001",
  year =         "2001",
  editor =       "Julian F. Miller and Marco Tomassini and 
                 Pier Luca Lanzi and Conor Ryan and Andrea G. B. Tettamanzi and 
                 William B. Langdon",
  volume =       "2038",
  series =       "LNCS",
  pages =        "143--159",
  address =      "Lake Como, Italy",
  publisher_address = "Berlin",
  month =        "18-20 " # apr,
  organisation = "EvoNET",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming, Schema
                 theory, Crossover, Subtree-swapping Crossover, Standard
                 Crossover, Evolution of size, Bloat, Variable-length
                 Genetic Algorithms",
  ISBN =         "3-540-41899-7",
  URL =          "",
  DOI =          "doi:10.1007/3-540-45355-5_12",
  size =         "17 pages",
  abstract =     "In this paper a new, general and exact schema theory
                 for genetic programming is presented. The theory
                 includes a microscopic schema theorem applicable to
                 crossover operators which replace a subtree in one
                 parent with a subtree from the other parent to produce
                 the offspring. A more macroscopic schema theorem is
                 also provided which is valid for crossover operators in
                 which the probability of selecting any two crossover
                 points in the parents depends only on their size and
                 shape. The theory is based on the notions of Cartesian
                 node reference systems and variable-arity hyperschemata
                 both introduced here for the first time. In the paper
                 we provide examples which show how the theory can be
                 specialised to specific crossover operators and how it
                 can be used to derive an exact definition of effective
                 fitness and a size-evolution equation for GP.",
  notes =        "EuroGP'2001, part of \cite{miller:2001:gp}",

Genetic Programming entries for Riccardo Poli