Fitness Evaluation Avoidance in Boolean GP Problems

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{jackson:2005:CEC,
  author =       "David Jackson",
  title =        "Fitness Evaluation Avoidance in {Boolean} GP
                 Problems",
  booktitle =    "Proceedings of the 2005 IEEE Congress on Evolutionary
                 Computation",
  year =         "2005",
  editor =       "David Corne and Zbigniew Michalewicz and 
                 Marco Dorigo and Gusz Eiben and David Fogel and Carlos Fonseca and 
                 Garrison Greenwood and Tan Kay Chen and 
                 Guenther Raidl and Ali Zalzala and Simon Lucas and Ben Paechter and 
                 Jennifier Willies and Juan J. Merelo Guervos and 
                 Eugene Eberbach and Bob McKay and Alastair Channon and 
                 Ashutosh Tiwari and L. Gwenn Volkert and 
                 Dan Ashlock and Marc Schoenauer",
  volume =       "3",
  pages =        "2530--2536",
  address =      "Edinburgh, UK",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  month =        "2-5 " # sep,
  organisation = "IEEE Computational Intelligence Society, Institution
                 of Electrical Engineers (IEE), Evolutionary Programming
                 Society (EPS)",
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-7803-9363-5",
  DOI =          "doi:10.1109/CEC.2005.1555011",
  size =         "7 pages",
  abstract =     "A technique has been devised which, via consideration
                 of the program nodes executed during fitness
                 evaluation, allows a genetic programming system to
                 determine many instances in which invocation of the
                 fitness function can be avoided. The nature of Boolean
                 logic problems renders them of particular interest as a
                 focus of study for the application of this technique,
                 and experimental evidence shows that significant
                 speed-ups in execution time can be achieved when
                 evolving solutions to these problems.",
  notes =        "CEC2005 - A joint meeting of the IEEE, the IEE, and
                 the EPS.

                 Santa Fe Ant, 6-mux, 5-parity. Visit tree. ~2 fold
                 speed up. 2.8GHz pentium 500 6-mux 50-gens runs
                 6-10mins in total. AND, OR, NOT, IF",
}

Genetic Programming entries for David Jackson

Citations