The Importance of Being Flat-Studying the Program Length Distributions of Operator Equalisation

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Sara Silva and Leonardo Vanneschi",
  title =        "The Importance of Being Flat-Studying the Program
                 Length Distributions of Operator Equalisation",
  booktitle =    "Genetic Programming Theory and Practice IX",
  year =         "2011",
  editor =       "Rick Riolo and Ekaterina Vladislavleva and 
                 Jason H. Moore",
  series =       "Genetic and Evolutionary Computation",
  address =      "Ann Arbor, USA",
  month =        "12-14 " # may,
  publisher =    "Springer",
  chapter =      "12",
  pages =        "211--233",
  keywords =     "genetic algorithms, genetic programming, Bloat,
                 Operator Equalisation, Crossover Bias, Program Length
  isbn13 =       "978-1-4614-1769-9",
  DOI =          "doi:10.1007/978-1-4614-1770-5_12",
  abstract =     "The recent Crossover Bias theory has shown that bloat
                 in Genetic Programming can be caused by the
                 proliferation of small unfit individuals in the
                 population. Inspired by this theory, Operator
                 Equalisation is the most recent and successful bloat
                 control method available. In a recent work there has
                 been an attempt to replicate the evolutionary dynamics
                 of Operator Equalisation by joining two key ingredients
                 found in older and newer bloat control methods.
                 However, the obtained dynamics was very different from
                 expected, which prompted a further investigation into
                 the reasons that make Operator Equalisation so
                 successful. It was revealed that, at least for complex
                 symbolic regression problems, the distribution of
                 program lengths enforced by Operator Equalisation is
                 nearly flat, contrasting with the peaky and well
                 delimited distributions of the other approaches. In
                 this work we study the importance of having flat
                 program length distributions for bloat control. We
                 measure the flatness of the distributions found in
                 previous and new Operator Equalisation variants and we
                 correlate it with the amount of search performed by
                 each approach. We also analyse where this search occurs
                 and how bloat correlates to these properties. We
                 conclude presenting a possible explanation for the
                 unique behaviour of Operator Equalisation.",
  notes =        "part of \cite{Riolo:2011:GPTP}",
  affiliation =  "KDBIOgroup, INESC-IDLisboa, Coimbra, Portugal",

Genetic Programming entries for Sara Silva Leonardo Vanneschi