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Fighting Bloat with Nonparametric Parsimony Pressure

  • Sean Luke
  • Liviu Panait
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2439)

Abstract

Many forms of parsimony pressure are parametric, that is final fitness is a parametric model of the actual size and raw fitness values. The problem with parametric techniques is that they are hard to tune to prevent size from dominating fitness late in the evolutionary run, or to compensate for problem-dependent nonlinearities in the raw fitness function. In this paper we briefly discuss existing bloat-control techniques, then introduce two new kinds of non-parametric parsimony pressure, Direct and Proportional Tournament. As their names suggest, these techniques are based on simple modifications of tournament selection to consider both size and fitness, but not together as a combined parametric equation. We compare the techniques against, and in combination with, the most popular genetic programming bloat-control technique, Koza-style depth limiting, and show that they are effective in limiting size while still maintaining good best-fitness-of-run results.

Keywords

Genetic Programming Tree Size Tournament Selection Linear Genetic Programming Genetic Programming System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Sean Luke
    • 1
  • Liviu Panait
    • 1
  1. 1.Department of Computer ScienceGeorge Mason UniversityFairfaxUSA

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