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A Data Structure for Improved GP Analysis via Efficient Computation and Visualisation of Population Measures

  • Anikó Ekárt
  • Steven Gustafson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3003)

Abstract

Population measures for genetic programs are defined and analysed in an attempt to better understand the behaviour of genetic programming. Some measures are simple, but do not provide sufficient insight. The more meaningful ones are complex and take extra computation time. Here we present a unified view on the computation of population measures through an information hyper-tree (iTree). The iTree allows for a unified and efficient calculation of population measures via a basic tree traversal.

Keywords

Genetic Programming Edit Distance Genetic Tree Population Measure Sparse Tree 
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

  • Anikó Ekárt
    • 1
  • Steven Gustafson
    • 2
  1. 1.Computer and Automation Research Institute, Hungarian Academy of SciencesBudapestHungary
  2. 2.School of Computer Science & ITUniversity of NottinghamNottinghamUnited Kingdom

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