Performance enhanced genetic programming

  • Chris Clack
  • Tina Yu
Genetic Programming: Issues and Applications

DOI: 10.1007/BFb0014803

Part of the Lecture Notes in Computer Science book series (LNCS, volume 1213)
Cite this paper as:
Clack C., Yu T. (1997) Performance enhanced genetic programming. In: Angeline P.J., Reynolds R.G., McDonnell J.R., Eberhart R. (eds) Evolutionary Programming VI. EP 1997. Lecture Notes in Computer Science, vol 1213. Springer, Berlin, Heidelberg

Abstract

Genetic Programming is increasing in popularity as the basis for a wide range of learning algorithms. However, the technique has to date only been successfully applied to modest tasks because of the performance overheads of evolving a large number of data structures, many of which do not correspond to a valid program. We address this problem directly and demonstrate how the evolutionary process can be achieved with much greater efficiency through the use of a formally-based representation and strong typing. We report initial experimental results which demonstrate that our technique exhibits significantly better performance than previous work.

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Copyright information

© Springer-Verlag 1997

Authors and Affiliations

  • Chris Clack
    • 1
  • Tina Yu
    • 1
  1. 1.Department of Computer ScienceUniversity College LondonLondonEngland

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