Using genetic programming to discover nonlinear variable interactions

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Chris Westbury and Lori Buchanan and 
                 Michael Sanderson and Mijke Rhemtulla and Leah Phillips",
  title =        "Using genetic programming to discover nonlinear
                 variable interactions",
  journal =      "Behavior Research Methods, Instruments, \& Computers",
  year =         "2003",
  volume =       "35",
  number =       "2",
  pages =        "202--216",
  month =        may,
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "0743-3808",
  publisher =    "Springer-Verlag",
  URL =          "",
  DOI =          "doi:10.3758/BF03202543",
  size =         "15 pages",
  abstract =     "Psychology has to deal with many interacting
                 variables. The analyses usually used to uncover such
                 relationships have many constraints that limit their
                 utility. We briefly discuss these and describe recent
                 work that uses genetic programming to evolve equations
                 to combine variables in nonlinear ways in a number of
                 different domains. We focus on four studies of
                 interactions from lexical access experiments and
                 psychometric problems. In all cases, genetic
                 programming described nonlinear combinations of items
                 in a manner that was subsequently independently
                 verified. We discuss the general implications of
                 genetic programming and related computational methods
                 for multivariate problems in psychology",
  notes =        "PMID: 12834075",

Genetic Programming entries for Chris Westbury Lori Buchanan Michael Sanderson Mijke Rhemtulla Leah Phillips