Solving Uncompromising Problems with Lexicase Selection

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Thomas Helmuth and Lee Spector and James Matheson",
  title =        "Solving Uncompromising Problems with Lexicase
  journal =      "IEEE Transactions on Evolutionary Computation",
  year =         "2015",
  volume =       "19",
  number =       "5",
  pages =        "630--643",
  month =        oct,
  keywords =     "genetic algorithms, genetic programming, parent
                 selection, lexicase selection, tournament selection,
  ISSN =         "1089-778X",
  URL =          "",
  DOI =          "doi:10.1109/TEVC.2014.2362729",
  size =         "14 pages",
  abstract =     "We describe a broad class of problems, called
                 uncompromising problems, characterised by the
                 requirement that solutions must perform optimally on
                 each of many test cases. Many of the problems that have
                 long motivated genetic programming research, including
                 the automation of many traditional programming tasks,
                 are uncompromising. We describe and analyse the
                 recently proposed lexicase parent selection algorition
                 and show that it can facilitate the solution of
                 uncompromising problems by genetic programming. Unlike
                 most traditional parent selection techniques, lexicase
                 selection does not base selection on a fitness value
                 that is aggregated over all test cases; rather, it
                 considers test cases one at a time in random order. We
                 present results comparing lexicase selection to more
                 traditional parent selection methods, including
                 standard tournament selection and implicit fitness
                 sharing, on four uncompromising problems: finding terms
                 in finite algebras, designing digital multipliers,
                 counting words in files, and performing symbolic
                 regression of the factorial function. We provide
                 evidence that lexicase selection maintains higher
                 levels of population diversity than other selection
                 methods, which may partially explain its utility as a
                 parent selection algorithm in the context of
                 uncompromising problems.",
  notes =        "tree-based GP

                 Also known as \cite{6920034}",

Genetic Programming entries for Thomas Helmuth Lee Spector James Matheson