Implicitly Controlling Bloat in Genetic Programming

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

@Article{Whigham:2010:ieeeTEC,
  author =       "Peter A. Whigham and Grant Dick",
  title =        "Implicitly Controlling Bloat in Genetic Programming",
  journal =      "IEEE Transactions on Evolutionary Computation",
  year =         "2010",
  volume =       "14",
  number =       "2",
  pages =        "173--190",
  month =        apr,
  keywords =     "genetic algorithms, genetic programming, Bloat, Book
                 reviews, Convergence, Data mining, Mathematical model,
                 Pediatrics, elitism, inbreeding, spatially-structured
                 evolutionary algorithm",
  ISSN =         "1089-778X",
  DOI =          "doi:10.1109/TEVC.2009.2027314",
  size =         "18 pages",
  abstract =     "During the evolution of solutions using genetic
                 programming (GP) there is generally an increase in
                 average tree size without a corresponding increase in
                 fitness---a phenomenon commonly referred to as bloat.
                 Although previously studied from theoretical and
                 practical viewpoints there has been little progress in
                 deriving controls for bloat which do not explicitly
                 refer to tree size. Here, the use of spatial population
                 structure in combination with local elitist replacement
                 is shown to reduce bloat without a subsequent loss of
                 performance. Theoretical concepts regarding inbreeding
                 and the role of elitism are used to support the
                 described approach. The proposed system behavior is
                 confirmed via extensive computer simulations on
                 benchmark problems. The main practical result is that
                 by placing a population on a torus, with selection
                 defined by a Moore neighborhood and local elitist
                 replacement, bloat can be substantially reduced without
                 compromising performance.",
  notes =        "also known as \cite{5352336}",
}

Genetic Programming entries for Peter Alexander Whigham Grant Dick

Citations