A Self-Tuning Mechanism for Depth-Dependent Crossover

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Takuya Ito and Hitoshi Iba and Satoshi Sato",
  title =        "A Self-Tuning Mechanism for Depth-Dependent
  booktitle =    "Advances in Genetic Programming 3",
  publisher =    "MIT Press",
  year =         "1999",
  editor =       "Lee Spector and William B. Langdon and 
                 Una-May O'Reilly and Peter J. Angeline",
  chapter =      "16",
  pages =        "377--399",
  address =      "Cambridge, MA, USA",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-262-19423-6",
  URL =          "http://www.cs.bham.ac.uk/~wbl/aigp3/ch16.pdf",
  abstract =     "There are three genetic operators: crossover, mutation
                 and reproduction in Genetic Programming (GP). Among
                 these genetic operators, the crossover operator mainly
                 contributes to searching for a solution program.
                 Therefore, we aim at improving the program generation
                 by extending the crossover operator. The normal
                 crossover selects crossover points randomly and
                 destroys building blocks. We think that building blocks
                 can be protected by swapping larger substructures. In
                 our former work, we proposed a depth-dependent
                 crossover. The depth-dependent crossover protected
                 building blocks and constructed larger building blocks
                 easily by swapping shallower nodes. However, there was
                 problem-dependent characteristics on the
                 depth-dependent crossover, because the depth selection
                 probability was fixed for all nodes in a tree. To solve
                 this difficulty, we propose a self-tuning mechanism for
                 the depth selection probability. We call this type of
                 crossover a {"}self-tuning depth-dependent
                 crossover{"}. We compare GP performances of the
                 selftuning depthdependent crossover with performances
                 of the original depth-dependent crossover. Our
                 experimental results clarify the superiority of the
                 self tuning depth dependent crossover.",
  notes =        "AiGP3 See http://cognet.mit.edu

                 11 mux, santa fe ant, 4-even parity, simulated robot",

Genetic Programming entries for Takuya Ito Hitoshi Iba Satoshi Sato