Context preserving crossover in genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@InProceedings{Dhaeseleer:1994:cpcGP,
  author =       "Patrik D'haeseleer",
  title =        "Context preserving crossover in genetic programming",
  booktitle =    "Proceedings of the 1994 IEEE World Congress on
                 Computational Intelligence",
  year =         "1994",
  volume =       "1",
  pages =        "256--261",
  address =      "Orlando, Florida, USA",
  month =        "27-29 " # jun,
  publisher =    "IEEE Press",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/ftp.io.com/papers/WCCI94_CPC.ps.Z",
  URL =          "http://www.cs.unm.edu/~patrik/WCCI94_CPC.mac.ps",
  URL =          "http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=00350006",
  doi =          "doi:10.1109/ICEC.1994.350006",
  keywords =     "genetic algorithms, genetic programming, S-expression
                 tree, context-preserving crossover, crossover
                 operators, matching coordinates, node coordinate
                 scheme, subtrees,optimisation, path planning,
                 programming, trees (mathematics)",
  size =         "6 pages",
  abstract =     "This paper introduces two new crossover operators for
                 Genetic Programming (GP). Contrary to the regular GP
                 crossover, the operators presented attempt to preserve
                 the context in which subtrees appeared in the parent
                 trees. A simple coordinate scheme for nodes in an
                 S-expression tree is proposed, and crossovers are only
                 allowed between nodes with exactly or partially
                 matching coordinates.",
  notes =        "Two new crossover operators for GP (Strong Context
                 preserving (SCPC) and Weak context preserving(WCPC)).
                 These attempt to preserve the context of swapped
                 subtrees. SCPC best used 50percent with Koza crossover.
                 100percent WCPC not performing as well.

                 Obstacle avoiding (simulated) robot, 11-multiplexor,
                 food foraging.

                 ",
}

Genetic Programming entries for Patrik D'haeseleer