Investigating the Baldwin Effect on Cartesian Genetic Programming Efficiency

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

  author =       "Mehrdad Khatir and Amir Hossein Jahangir and 
                 Hamid Beigy",
  title =        "Investigating the Baldwin Effect on Cartesian Genetic
                 Programming Efficiency",
  booktitle =    "2008 IEEE World Congress on Computational
  year =         "2008",
  editor =       "Jun Wang",
  pages =        "2360--2364",
  address =      "Hong Kong",
  month =        "1-6 " # jun,
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  isbn13 =       "978-1-4244-1823-7",
  file =         "EC0549.pdf",
  DOI =          "doi:10.1109/CEC.2008.4631113",
  abstract =     "Cartesian Genetic Programming (CGP) has an unusual
                 genotype representation which makes it more efficient
                 than Genetic programming (GP) in digital circuit design
                 problem. However, to the best of our knowledge, all
                 methods used in evolutionary design of digital circuits
                 deal with rugged, complex search space, which results
                 in long running time to obtain successful evolution.
                 Therefore, employing a method to guide evolution in
                 these spaces can facilitate achieving more reasonable
                 results. It has been claimed that a two-step
                 evolutionary scenario caused by benefit and cost of
                 learning called Baldwin effect can guide evolution in
                 the biology and artificial life. Therefore, we have
                 been motivated to examine this effect on CGP. We
                 observe using this scenario the success rate and
                 evolution time of CGP improves dramatically especially
                 when size of chromosomes increases.",
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 Genetic Programming, Baldwin Effect, Phenotypic
                 Plasticity, Digital Circuit, Reinforcement Learning.",
  notes =        "WCCI 2008 - A joint meeting of the IEEE, the INNS, the
                 EPS and the IET.",

Genetic Programming entries for Mehrdad Khatir Amir Hossein Jahangir Hamid Beigy