Parsimony pressure made easy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

36 Scopus citations

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 [26] and rewrite it in a form that shows its direct relationship to Price's 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.

Original languageEnglish (US)
Title of host publicationGECCO'08
Subtitle of host publicationProceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008
PublisherAssociation for Computing Machinery (ACM)
Pages1267-1274
Number of pages8
ISBN (Print)9781605581309
DOIs
StatePublished - 2008
Event10th Annual Genetic and Evolutionary Computation Conference, GECCO 2008 - Atlanta, GA, United States
Duration: Jul 12 2008Jul 16 2008

Publication series

NameGECCO'08: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008

Other

Other10th Annual Genetic and Evolutionary Computation Conference, GECCO 2008
Country/TerritoryUnited States
CityAtlanta, GA
Period7/12/087/16/08

Keywords

  • Bloat
  • Genetic programming
  • Parsimony pressure

Fingerprint

Dive into the research topics of 'Parsimony pressure made easy'. Together they form a unique fingerprint.

Cite this