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Evolution of neural net architectures by a hierarchical grammar-based genetic system

  • Christian Jacob
  • Jan Rehder

Abstract

We present a hierarchically structured system for the evolution of connectionist systems. Our approach is exemplified by evolution paradigms for neural network topologies and weights. Our descriptions of a network’s connectivity are based on context-free grammars which are used to characterize signal flow from input to output neurons. Evolution of a simple control task gives a first impression about the capabilities of this approach.

Keywords

Output Neuron Cortex Neuron Neuron Functionality Neural Network Development Neuron Activation Function 
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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References

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Copyright information

© Springer-Verlag/Wien 1993

Authors and Affiliations

  • Christian Jacob
    • 1
  • Jan Rehder
    • 1
  1. 1.Universität Erlangen-NürnbergErlangenGermany

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