Slightly Beyond Turing's Computability for Studying Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4202

  author =       "Olivier Teytaud",
  title =        "Slightly Beyond {Turing}'s Computability for Studying
                 Genetic Programming",
  booktitle =    "Proceedings of the 5th International Conference on
                 Machines, Computations, and Universality, MCU 2007",
  year =         "2007",
  editor =       "J{\'e}r{\^o}me Olivier Durand-Lose and 
                 Maurice Margenstern",
  volume =       "4664",
  series =       "Lecture Notes in Computer Science",
  pages =        "279--290",
  address =      "Orl{\'e}ans, France",
  month =        sep # " 10-13",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-540-74592-1",
  DOI =          "doi:10.1007/978-3-540-74593-8_24",
  size =         "12 pages",
  abstract =     "Inspired by genetic programming (GP), we study
                 iterative algorithms for non-computable tasks and
                 compare them to naive models. This framework justifies
                 many practical standard tricks from GP and also
                 provides complexity lower-bounds which justify the
                 computational cost of GP thanks to the use of
                 Kolmogorov's complexity in bounded time.",
  notes =        "Symbolic regression",
  bibdate =      "2007-08-28",
  bibsource =    "DBLP,

Genetic Programming entries for Olivier Teytaud