Optimal Neuron Selection and Generalization: NK Ensemble Neural Networks

  • Darrell Whitley
  • Renato Tinós
  • Francisco Chicano
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11102)


This paper explores how learning can be achieved by turning on and off neurons in a special hidden layer of a neural network. By posing the neuron selection problem as a pseudo-Boolean optimization problem with bounded tree width, an exact global optimum can be obtained to the neuron selection problem in O(N) time. To illustrate the effectiveness of neuron selection, the method is applied to optimizing a modified Echo State Network for two learning problems: (1) Mackey-Glass time series prediction and (2) a reinforcement learning problem using a recurrent neural network. Empirical tests indicate that neuron selection results in rapid learning and, more importantly, improved generalization.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Darrell Whitley
    • 1
  • Renato Tinós
    • 2
  • Francisco Chicano
    • 3
  1. 1.Colorado State UniversityFort CollinsUSA
  2. 2.University of São PauloRibeirão PretoBrazil
  3. 3.University of MálagaMálagaSpain

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