Reconfigurable analogue hardware evolution of adaptive spiking neural network controllers

  • Authors:
  • Brian McGinley;Patrick Rocke;Fearghal Morgan;John Maher

  • Affiliations:
  • National University of Ireland, Galway, Galway, Ireland;National University of Ireland, Galway, Galway, Ireland;National University of Ireland, Galway, Galway, Ireland;National University of Ireland, Galway, Galway, Ireland

  • Venue:
  • Proceedings of the 10th annual conference on Genetic and evolutionary computation
  • Year:
  • 2008

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Abstract

This paper details the hardware evolution of adaptive Spiking Neural Network (SNN) controllers, implemented on a network of cascaded Field Programmable Analogue Arrays (FPAAs). The fixed architecture, feed forward SNNs are trained using a Genetic Algorithm (GA). An obstacle avoidance simulated robotics controller application is chosen to test the FPAA reconfigurable hardware evolution platform. Evolved behaviours, resulting from FPAA-based SNN controllers, are compared with those obtained using software-based SNN implementations. Results presented indicate the emergence of effective behaviours and adaptation to environmental change.