Evolving recurrent models using linear GP

  • Authors:

  • Xiao Luo;Malcolm I. Heywood;A. Nur Zincir-Heywood

  • Affiliations:

  • Dalhousie University, Halifax, Canada;Dalhousie University, Halifax, Canada;Dalhousie University, Halifax, Canada

  • Venue:
  • GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
  • Year:
  • 2005

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Abstract

Turing complete Genetic Programming (GP) models introduce the concept of internal state, and therefore have the capacity for identifying interesting temporal properties. Surprisingly, there is little evidence of the application of such models to problems for prediction. An empirical evaluation is made of a simple recurrent linear GP model over standard prediction problems.