Running programs backwards: instruction inversion for effective search in semantic spaces

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

  author =       "Bartosz Wieloch and Krzysztof Krawiec",
  title =        "Running programs backwards: instruction inversion for
                 effective search in semantic spaces",
  booktitle =    "GECCO '13: Proceeding of the fifteenth annual
                 conference on Genetic and evolutionary computation
  year =         "2013",
  editor =       "Christian Blum and Enrique Alba and Anne Auger and 
                 Jaume Bacardit and Josh Bongard and Juergen Branke and 
                 Nicolas Bredeche and Dimo Brockhoff and 
                 Francisco Chicano and Alan Dorin and Rene Doursat and 
                 Aniko Ekart and Tobias Friedrich and Mario Giacobini and 
                 Mark Harman and Hitoshi Iba and Christian Igel and 
                 Thomas Jansen and Tim Kovacs and Taras Kowaliw and 
                 Manuel Lopez-Ibanez and Jose A. Lozano and Gabriel Luque and 
                 John McCall and Alberto Moraglio and 
                 Alison Motsinger-Reif and Frank Neumann and Gabriela Ochoa and 
                 Gustavo Olague and Yew-Soon Ong and 
                 Michael E. Palmer and Gisele Lobo Pappa and 
                 Konstantinos E. Parsopoulos and Thomas Schmickl and Stephen L. Smith and 
                 Christine Solnon and Thomas Stuetzle and El-Ghazali Talbi and 
                 Daniel Tauritz and Leonardo Vanneschi",
  isbn13 =       "978-1-4503-1963-8",
  pages =        "1013--1020",
  keywords =     "genetic algorithms, genetic programming",
  month =        "6-10 " # jul,
  organisation = "SIGEVO",
  address =      "Amsterdam, The Netherlands",
  DOI =          "doi:10.1145/2463372.2463493",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "The instructions used for solving typical genetic
                 programming tasks have strong mathematical properties.
                 In this study, we leverage one of such properties:
                 invertibility. A search operator is proposed that
                 performs an approximate reverse execution of program
                 fragments, trying to determine in this way the desired
                 semantics (partial outcome) at intermediate stages of
                 program execution. The desired semantics determined in
                 this way guides the choice of a subprogram that
                 replaces the old program fragment. An extensive
                 computational experiment on 20 symbolic regression and
                 Boolean domain problems leads to statistically
                 significant evidence that the proposed Random Desired
                 Operator outperforms all typical combinations of
                 conventional mutation and crossover operators.",
  notes =        "Also known as \cite{2463493} GECCO-2013 A joint
                 meeting of the twenty second international conference
                 on genetic algorithms (ICGA-2013) and the eighteenth
                 annual genetic programming conference (GP-2013)",

Genetic Programming entries for Bartosz Wieloch Krzysztof Krawiec