Statistical exploratory analysis of genetic algorithms: the influence of gray codes upon the difficulty of a problem

  • Authors:

  • Andrew Czarn;Cara MacNish;Kaipillil Vijayan;Berwin Turlach

  • Affiliations:

  • School of Computer Science and Software Engineering, The University of Western Australia, Crawley, WA;School of Computer Science and Software Engineering, The University of Western Australia, Crawley, WA;School of Mathematics and Statistics, The University of Western Australia, Crawley, WA;School of Mathematics and Statistics, The University of Western Australia, Crawley, WA

  • Venue:
  • AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
  • Year:
  • 2004

Quantified Score

Hi-index 0.00

Visualization

Abstract

An important issue in genetic algorithms is the relationship between the difficulty of a problem and the choice of encoding Two questions remain unanswered: is their a statistically demonstrable relationship between the difficulty of a problem and the choice of encoding, and, if so, what it the actual mechanism by which this occurs? In this paper we use components of a rigorous statistical methodology to demonstrate that the choice of encoding has a real effect upon the difficulty of a problem Computer animation is then used to illustrate the actual mechanism by which this occurs.