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The Importance of Local Search

A Grammar Based Approach to Environmental Time Series Modelling
  • Tuan Hao Hoang
  • Xuan Nguyen
  • R I McKay
  • Daryl Essam
Part of the Genetic Programming book series (GPEM, volume 9)

Abstract

Standard Genetic Programming operators are highly disruptive, with the concomitant risk that it may be difficult to converge to an optimal structure. The Tree Adjoining Grammar (TAG) formalism provides a more flexible Genetic Programming tree representation which supports a wide range of operators while retaining the advantages of tree-based representation. In particular, minimal-change point insertion and deletion operators may be defined. Previous work has shown that point insertion and deletion, used as local search operators, can dramatically reduce search effort in a range of standard problems. Here, we evaluate the effect of local search with these operators on a real-World ecological time series modelling problem. For the same search effort, TAG-based GP with the local search operators generates solutions with significantly lower training set error. The results are equivocal on test set error, local search generating larger individuals which generalise only a little better than the less accurate solutions given by the original algorithm.

Keywords

local search insertion deletion grammar guided tree adjoining grammar ecological modelling time series 

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Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • Tuan Hao Hoang
    • 1
  • Xuan Nguyen
    • 1
  • R I McKay
    • 2
  • Daryl Essam
    • 2
  1. 1.Department of Information TechnologyMilitary Technical AcademyHanoiVietnam
  2. 2.School of Information Technology and Electrical EngineeringUniversity of New South Wales at the Australian Defence Force AcademyCanberraAustralia

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