Fitness Landscape Analysis and Image Filter Evolution Using Functional-Level CGP

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

  author =       "Karel Slan\'y and Luk\'as Sekanina",
  title =        "Fitness Landscape Analysis and Image Filter Evolution
                 Using Functional-Level CGP",
  editor =       "Marc Ebner and Michael O'Neill and Anik\'o Ek\'art and 
                 Leonardo Vanneschi and Anna Isabel Esparcia-Alc\'azar",
  booktitle =    "Proceedings of the 10th European Conference on Genetic
  publisher =    "Springer",
  series =       "Lecture Notes in Computer Science",
  volume =       "4445",
  year =         "2007",
  address =      "Valencia, Spain",
  month =        "11-13 " # apr,
  pages =        "311--320",
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming",
  ISBN =         "3-540-71602-5",
  isbn13 =       "978-3-540-71602-0",
  DOI =          "doi:10.1007/978-3-540-71605-1_29",
  abstract =     "This work analyses fitness landscapes for the image
                 filter design problem approached using functional-level
                 Cartesian Genetic Programming. Smoothness and
                 ruggedness of fitness landscapes are investigated for
                 five genetic operators. It is shown that the mutation
                 operator and the single-point crossover operator
                 generate the smoothest landscapes and thus they are
                 useful for practical applications in this area. In
                 contrast to the gate-level evolution, a destructive
                 behaviour of a simple crossover operator has not been
  notes =        "Part of \cite{ebner:2007:GP} EuroGP'2007 held in
                 conjunction with EvoCOP2007, EvoBIO2007 and

Genetic Programming entries for Karel Slany Lukas Sekanina