Random tree generation for genetic programming

  • Hitoshi Iba
Theoretical Foundations of Evolutionary Computation
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1141)


This paper introduces a random tree generation algorithm for GP (Genetic Programming). Generating random trees is an essential part of GP. However, the recursive method commonly used in GP does not necessarily generate random trees, i.e the standard GP initialization procedure does not sample the space of possible initial trees uniformly. This paper proposes a truly random tree generation procedure for GP. Our approach is grounded upon a bijection method, i.e., a 1–1 correspondence between a tree with n nodes and some simple word composed by letters x and y. We show how to use this correspondence to generate a GP tree and how GP search is improved by using this “randomness”.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Hitoshi Iba
    • 1
  1. 1.Machine Inference SectionElectrotechnical Laboratory (ETL)IbarakiJapan

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