Logic Function Induction with the Blender Algorithm Using Function Stacks

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

@InProceedings{Ashlock:2009:ANNIE,
  author =       "Daniel Ashlock and Douglas McCorkle and 
                 Kenneth M. Bryden",
  title =        "Logic Function Induction with the Blender Algorithm
                 Using Function Stacks",
  booktitle =    "ANNIE 2009, Intelligent Engineering Systems through
                 Artificial Neural Networks",
  year =         "2009",
  editor =       "Cihan H. Dagli and K. Mark Bryden and 
                 Steven M. Corns and Mitsuo Gen and Kagan Tumer and Gursel Suer",
  volume =       "19",
  pages =        "189--196",
  address =      "St. Louis, MO, USA",
  note =         "Part III Evolutionary Computation",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "9780791802953",
  DOI =          "doi:10.1115/1.802953.paper24",
  abstract =     "This paper applies two techniques, hybridisation and
                 small population effects, to the problem of logic
                 function induction. It also uses an efficient
                 representation for genetic programming called a
                 function stack. Function stacks are a directed acyclic
                 graph representation used in place of the more common
                 tree-structured representation. This study is the
                 second exploring an algorithm for evolutionary
                 computation called the blender algorithm which performs
                 hybridization of many small populations. The blender
                 algorithm is tested on the 3 and 4 variable parity
                 problems. Confirming and sharpening earlier results on
                 the use of small population sizes for the parity
                 problem, it is demonstrated that subpopulation size and
                 intervals between population mixing steps are critical
                 parameters. The blender algorithm is found to perform
                 well on the parity problem.",
}

Genetic Programming entries for Daniel Ashlock Douglas S McCorkle Kenneth M Bryden

Citations