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Discovery of Symbolic, Neuro-Symbolic and Neural Networks with Parallel Distributed Genetic Programming

Abstract

Parallel Distributed Genetic Programming (PDGP) is a new form of genetic programming suitable for the development of parallel programs in which symbolic and neural processing elements can be combined in a free and natural way. This paper describes the representation for programs and the genetic operators on which PDGP is based. Experimental results on the XOR problem axe also reported.

Keywords

Genetic Programming Parallel Program Active Node Genetic Operator Fitness Evaluation 
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 Wien 1998

Authors and Affiliations

  • R. Poli
    • 1
  1. 1.School of Computer ScienceThe University of BirminghamBirminghamUK

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