Fast Grammar-Based Evolution Using Memoization

  • Martin Luerssen
  • David Powers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6239)

Abstract

A streamlined, open-source implementation of Shared Grammar Evolution represents candidate solutions as grammars that can share production rules. It offers competitive search performance, while requiring little user-tuning of parameters. Uniquely, the system natively supports the memoization of return values computed during evaluation, which are stored with each rule and also shared between solutions. Significant improvements in evaluation time, up to 3.9-fold in one case, were observed when solving a set of classic GP problems – and even greater improvements can be expected for computation-intensive tasks. Additionally, the rule-based caching of intermediate representations, specifically of the terminal stack, was explored. It was shown to produce significant, although lesser speedups that were partly negated by computational overhead, but may be useful in dynamic and memory-bound tasks otherwise not amenable to memoization.

Keywords

Evolutionary algorithms genetic programming grammatical evolution shared grammar evolution memoization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Martin Luerssen
    • 1
  • David Powers
    • 1
  1. 1.Artificial Intelligence Laboratory, School of Computer Science, Engineering and MathematicsFlinders UniversityAdelaideAustralia

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