The Evolution of Size in Variable Length Representations

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

  author =       "W. B. Langdon",
  title =        "The Evolution of Size in Variable Length
  booktitle =    "1998 IEEE International Conference on Evolutionary
  year =         "1998",
  pages =        "633--638",
  address =      "Anchorage, Alaska, USA",
  month =        "5-9 " # may,
  organisation = "IEEE",
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, structural
                 complexity, introns, Price's Theorem, Santa Fe trail
                 problem, artificial ant, bloat, code growth,
                 competition, fluff, increasing structural complexity,
                 length bias, length-neutral mutation,
                 nonpopulation-based search techniques, population-based
                 search technique, program length increase, program
                 reproduction accuracy, search operators, simulated
                 annealing, size evolution, static evaluation functions,
                 strict hill climbing, subtree-based mutation operator,
                 tree sampling, tree size, unbiased mutation,
                 variable-length representations, competitive
                 algorithms, mathematical operators, programming theory,
                 search problems, simulated annealing, trees
                 (mathematics), variable length codes",
  ISBN =         "0-7803-4869-9",
  file =         "c109.pdf",
  URL =          "",
  URL =          "",
  DOI =          "doi:10.1109/ICEC.1998.700102",
  size =         "6 pages",
  abstract =     "In many cases programs length's increase (known as
                 'bloat', 'fluff' and increasing 'structural
                 complexity') during artificial evolution. We show bloat
                 is not specific to genetic programming and suggest it
                 is inherent in search techniques with discrete variable
                 length representations using simple static evaluation
                 functions. We investigate the bloating characteristics
                 of three non-population and one population based search
                 techniques using a novel mutation operator.

                 An artificial ant following the Santa Fe trail problem
                 is solved by simulated annealing, hill climbing, strict
                 hill climbing and population based search using two
                 variants of the the new subtree based mutation
                 operator. As predicted bloat is observed when using
                 unbiased mutation and is absent in simulated annealing
                 and both hill climbers when using the length neutral
                 mutation however bloat occurs with both mutations when
                 using a population.

                 We conclude that there are two causes of bloat 1)
                 search operators with no length bias tend to sample
                 bigger trees and 2) competition within populations
                 favours longer programs as they can usually reproduce
                 more accurately.",
  notes =        "ICEC-98 Held In Conjunction With WCCI-98 --- 1998 IEEE
                 World Congress on Computational Intelligence

                 based on \cite{langdon:1997:bloatSAHCP}",

Genetic Programming entries for William B Langdon