Recursion-Based Biases in Stochastic Grammar Model Genetic Programming

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

  author =       "Kangil Kim and R. I. (Bob) McKay and 
                 Nguyen Xuan Hoai",
  title =        "Recursion-Based Biases in Stochastic Grammar Model
                 Genetic Programming",
  journal =      "IEEE Transactions on Evolutionary Computation",
  year =         "2016",
  volume =       "20",
  number =       "1",
  pages =        "81--95",
  month =        feb,
  keywords =     "genetic algorithms, genetic programming, estimation of
                 distribution algorithm, EDA, EDA-GP, stochastic
                 context-free grammar, recursion depth, bias",
  ISSN =         "1089-778X",
  DOI =          "doi:10.1109/TEVC.2015.2425420",
  size =         "16 pages",
  abstract =     "Estimation of distribution algorithms applied to
                 genetic programming have been studied by a number of
                 authors. Like all estimation of distribution
                 algorithms, they suffer from biases induced by the
                 model building and sampling process. However, the
                 biases are amplified in the algorithms for genetic
                 programming. In particular, many systems use stochastic
                 grammars as their model representation, but biases
                 arise due to grammar recursion. We define and estimate
                 the bias due to recursion in grammar-based estimation
                 of distribution algorithms in genetic programming,
                 using methods derived from computational linguistics.
                 We confirm the extent of bias in some simple
                 experimental examples. We then propose some methods to
                 repair this bias. We apply the estimation of bias, and
                 its repair, to some more practical applications. We
                 experimentally demonstrate the extent of bias arising
                 from recursion, and the performance improvements that
                 can result from correcting it.",
  notes =        "Electronics and Telecommunications Research Institute,
                 Korea. Also known as \cite{7091890}",

Genetic Programming entries for Kangil Kim R I (Bob) McKay Nguyen Xuan Hoai