The effect of function noise on GP efficiency

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

@InCollection{lee:1995:efnGPe,
  author =       "Jack Y. B. Lee and P. C. Wong",
  title =        "The effect of function noise on GP efficiency",
  booktitle =    "Progress in Evolutionary Computation",
  publisher =    "Springer-Verlag",
  year =         "1995",
  editor =       "Xin Yao",
  volume =       "956",
  series =       "Lecture Notes in Artificial Intelligence",
  pages =        "1--16",
  address =      "Heidelberg, Germany",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-540-60154-8",
  DOI =          "doi:10.1007/3-540-60154-6_43",
  abstract =     "Genetic Programming (GP) has been applied to many
                 problems and there are indications [1,2,3] that GP is
                 potentially useful in evolving algorithms for problem
                 solving. This paper investigates one problem with
                 algorithmic evolution using GP - Function Noise. We
                 show that the performance of GP could be severely
                 degraded even in the presence of minor noise in the GP
                 functions. We investigated two counter noise schemes,
                 Multi-Sampling Function and Multi-Testcases. We show
                 that the Multi-Sampling Function scheme can reduce the
                 effect of noise in a predictable way while the
                 Multi-Test cases scheme evolves radically different
                 program structures to avoid the effect of noise.
                 Essentially, the two schemes lead the GP to evolve into
                 different approaches to solving the same problem.",
  size =         "16 pages",
  notes =        "Artificial ant on Santa Fe Trail with noisy
                 IfFoodAhead GP does poorly even with small amounts of
                 with noise. Sometimes population abandons use of
                 IfFoodAhead entirely (what else could it do?)

                 ",
  affiliation =  "The Chinese University of Hong Kong Advanced Network
                 Systems Laboratory Department of Information
                 Engineering Hongkong Hongkong",
}

Genetic Programming entries for Jack Y B Lee Po Choi Wong

Citations