Covariant Parsimony Pressure for Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "Riccardo Poli and Nicholas F. McPhee",
  title =        "Covariant Parsimony Pressure for Genetic Programming",
  institution =  "Department of Computing and Electronic Systems,
                 University of Essex",
  year =         "2008",
  number =       "CES-480",
  address =      "UK",
  month =        jan,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "",
  size =         "20 pages",
  abstract =     "The parsimony pressure method is perhaps the simplest
                 and most frequently used method to control bloat in
                 genetic programming. In this paper we first reconsider
                 the size evolution equation for genetic programming
                 developed in [24] and rewrite it in a form that shows
                 its direct relationship to Prices theorem. We then use
                 this new formulation to derive theoretical results that
                 show how to practically and optimally set the parsimony
                 coefficient dynamically during a run so as to achieve
                 complete control over the growth of the programs in a
                 population. Experimental results confirm the
                 effectiveness of the method, as we are able to tightly
                 control the average program size under a variety of
                 conditions. These include such unusual cases as
                 dynamically varying target sizes such that the mean
                 program size is allowed to grow during some phases of a
                 run, while being forced to shrink in others.",

Genetic Programming entries for Riccardo Poli Nicholas Freitag McPhee