Logic Function Induction with the Blender Algorithm Using Function Stacks

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@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",
• chapter = "24",
• 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