Uniform Linear Transformation with Repair and Alternation in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

  author =       "Lee Spector and Thomas Helmuth",
  title =        "Uniform Linear Transformation with Repair and
                 Alternation in Genetic Programming",
  booktitle =    "Genetic Programming Theory and Practice XI",
  year =         "2013",
  series =       "Genetic and Evolutionary Computation",
  editor =       "Rick Riolo and Jason H. Moore and Mark Kotanchek",
  publisher =    "Springer",
  chapter =      "8",
  pages =        "137--153",
  address =      "Ann Arbor, USA",
  month =        "9-11 " # may,
  keywords =     "genetic algorithms, genetic programming, Uniform
                 mutation, Uniform crossover, ULTRA, Push, PushGP, Drug
                 bioavailability problem, Pagie-1 problem, Factorial
                 regression, Boolean multiplexer problem",
  isbn13 =       "978-1-4939-0374-0",
  DOI =          "doi:10.1007/978-1-4939-0375-7_8",
  abstract =     "Several genetic programming researchers have argued
                 for the utility of genetic operators that act
                 uniformly. By act uniformly we mean two specific
                 things: that the probability of an inherited program
                 component being modified during inheritance is
                 independent of the size and shape of the parent
                 programs beyond the component in question; and that
                 pairs of parents are combined in ways that allow
                 arbitrary combinations of components from each parent
                 to appear in the child. Uniform operators described in
                 previous work have had limited utility, however,
                 because of a mismatch between the relevant notions of
                 uniformity and the hierarchical structure and variable
                 sizes of many genetic programming representations. In
                 this chapter we describe a new genetic operator, ULTRA,
                 which incorporates aspects of both mutation and
                 crossover and acts approximately uniformly across
                 programs of variable sizes and structures. ULTRA treats
                 hierarchical programs as linear sequences and includes
                 a repair step to ensure that syntax constraints are
                 satisfied after variation. We show that on the drug
                 bioavailability and Pagie-1 benchmark problems ULTRA
                 produces significant improvements both in
                 problem-solving power and in program size relative to
                 standard operators. Experiments with factorial
                 regression and with the Boolean 6-multiplexer problem
                 demonstrate that ULTRA can manipulate programs that
                 make use of hierarchical structure, but also that it is
                 not always beneficial. The demonstrations evolve
                 programs in the Push programming language, which makes
                 repair particularly simple, but versions of the
                 technique should be applicable in other genetic
                 programming systems as well.",
  notes =        "http://cscs.umich.edu/gptp-workshops/

                 Part of \cite{Riolo:2013:GPTP} published after the
                 workshop in 2013",

Genetic Programming entries for Lee Spector Thomas Helmuth