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Softening the Structural Difficulty in Genetic Programming with TAG-Based Representation and Insertion/Deletion Operators

  • Nguyen Xuan Hoai
  • R. I. McKay
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3103)

Abstract

In a series of papers [3-8], Daida et. al. highlighted the difficulties posed to Genetic Programming (GP) by the complexity of the structural search space, and attributed the problem to the expression tree representation in GP. In this paper, we show how to transform a fixed-arity expression tree in GP to a non fixed-arity tree (Catalan tree) using representation based on Tree Adjoining Grammars (TAGs). This non fixed-arity property, which is called feasibility, allows us to design many types of genetic operators (as in [16]). In particular, insertion/deletion operators arising naturally from the representation play a role as structural mutation operators. By using these dual operators on TAG-based representation, we demonstrate how these operators can help to soften the structural search difficulties in GP.

Keywords

Genetic Programming Derivation Tree Elementary Tree Expression Tree 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 2004

Authors and Affiliations

  • Nguyen Xuan Hoai
    • 1
  • R. I. McKay
    • 1
  1. 1.School of IT & EE, Australian Defence Force academyUniversity of New South WalesAustralia

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