Pre-, In- and Postfix grammars for Symbolic Regression in Grammatical Evolution

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

  author =       "Erik Hemberg and Nic McPhee and Michael O'Neill and 
                 Anthony Brabazon",
  title =        "Pre-, In- and Postfix grammars for Symbolic Regression
                 in Grammatical Evolution",
  booktitle =    "IEEE Workshop and Summer School on Evolutionary
  year =         "2008",
  editor =       "T. M. McGinnity",
  pages =        "18--22",
  address =      "University of Ulster, Derry, Northern Ireland",
  month =        "18-22 " # aug,
  keywords =     "genetic algorithms, genetic programming, Grammatical
  URL =          "",
  size =         "4 pages",
  abstract =     "Recent research has indicated that grammar design is
                 an important consideration when using grammar-based
                 Genetic Programming, particularly with respect to
                 unintended biases that may arise through rule ordering
                 or duplication. In this study we examine how the
                 ordering of the elements during mapping can impact
                 performance. Here we use to the standard GE depth-first
                 mapper and compare the performance of postfix, prefix
                 and infix grammars on a selection of symbolic
                 regression problem instances. We show that postfix can
                 confer a performance advantage on the harder problems
  notes =        "broken 2016

Genetic Programming entries for Erik Hemberg Nicholas Freitag McPhee Michael O'Neill Anthony Brabazon