Fitness Landscapes and Difficulty in Genetic Programming   [FL] [GP]

by

Kinnear, K., E. and Jr.

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Info: Proceedings of the 1994 IEEE World Conference on Computational Intelligence (Conference proceedings), 1994, p. 142-147
Keywords:genetic algorithms, genetic programming
Abstract:
This paper examines the fitness landscape [FL] in which GP operates and the landscapes of a range of problems of known difficulty are analyzed in an attempt to determing which landscape measures correlate with the difficulty of the problem.
Notes:
Defines difficulty as number of fitness cases/1000. Considers a few parity and sort problems. Fitness landscape investigated by using GP operators (without selection) on gen=0 to give a number of random walks. Look at autocorrelation of fitness along these walks. Essentially none (<0.5) very much worse than published GA. Also little correlation between this and difficulty measure.
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BibTex:
@InProceedings{ieee94:kinnear,
  author =       "Kenneth E. {Kinnear, Jr.}",
  title =        "Fitness Landscapes and Difficulty in Genetic
                 Programming",
  year =         "1994",
  booktitle =    "Proceedings of the 1994 IEEE World Conference on
                 Computational Intelligence",
  publisher =    "IEEE Press",
  volume =       "1",
  pages =        "142--147",
  address =      "Orlando, Florida, USA",
  month =        "27-29 " # jun,
  size =         "6 pages",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "ftp://ftp.mad-scientist.com/pub/genetic-programming/papers/kinnear.wcci.ps.Z",
  ISBN =         "0-7803-1899-4",
  abstract =     "This paper examines the fitness landscape in which GP
                 operates and the landscapes of a range of problems of
                 known difficulty are analyzed in an attempt to
                 determing which landscape measures correlate with the
                 difficulty of the problem.",
  notes =        "Defines difficulty as number of fitness cases/1000.
                 Considers a few parity and sort problems. Fitness
                 landscape investigated by using GP operators (without
                 selection) on gen=0 to give a number of random walks.
                 Look at autocorrelation of fitness along these walks.
                 Essentially none (<0.5) very much worse than published
                 GA. Also little correlation between this and difficulty
                 measure.

                 ",
}