Genetic programming with genetic regulatory networks

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

  author =       "Rui L. Lopes and Ernesto Costa",
  title =        "Genetic programming with genetic regulatory networks",
  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 =        "965--972",
  keywords =     "genetic algorithms, genetic programming, inverted
                 pendulum, artificial art",
  month =        "6-10 " # jul,
  organisation = "SIGEVO",
  address =      "Amsterdam, The Netherlands",
  DOI =          "doi:10.1145/2463372.2463488",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "Evolutionary Algorithms (EA) approach differently from
                 nature the genotype-phenotype relationship, and this
                 view is a recurrent issue among researchers. Recently,
                 some researchers have started exploring computationally
                 the new comprehension of the multitude of regulatory
                 mechanisms that are fundamental in both processes of
                 inheritance and of development in natural systems, by
                 trying to include those mechanisms in the EAs.

                 One of the first successful proposals was the
                 Artificial Regulatory Network (ARN) model. Soon after
                 some variants of the ARN, including different
                 improvements over the base model, were tested. In this
                 paper, we combine two of those alternatives,
                 demonstrating experimentally how the resulting model
                 can deal with complex problems, including those that
                 have multiple outputs. The efficacy and efficiency of
                 this variant are tested experimentally using two
                 benchmark problems that show how we can evolve a
                 controller or an artificial artist.",
  notes =        "Also known as \cite{2463488} 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 Rui Lopes Ernesto Costa