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Paladyn, Journal of Behavioral Robotics

Editor-in-Chief: Schöner, Gregor

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2081-4836
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Modular non-computational-connectionist-hybrid neural network approach to robotic systems *

C.D. Bamford / R.J. Mitchell
Published Online: 2012-03-12 | DOI: https://doi.org/10.2478/s13230-012-0003-6

Abstract

Spiking neural networks are usually limited in their applications due to their complex mathematical models and the lack of intuitive learning algorithms. In this paper, a simpler, novel neural network derived from a leaky integrate and fire neuron model, the ‘cavalcade’ neuron, is presented. A simulation for the neural network has been developed and two basic learning algorithms implemented within the environment. These algorithms successfully learn some basic temporal and instantaneous problems. Inspiration for neural network structures from these experiments are then taken and applied to process sensor information so as to successfully control a mobile robot.

Keywords: neural networks; robotics; spiking neurons; hybrid systems

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About the article


Received: 2011-11-11

Accepted: 2012-01-26

Published Online: 2012-03-12

Published in Print: 2011-09-01


Citation Information: Paladyn, Journal of Behavioral Robotics, ISSN (Online) 2081-4836, DOI: https://doi.org/10.2478/s13230-012-0003-6.

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© C.D. Bamford et al.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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