Table of Contents
Advances in Artificial Intelligence
Volume 2010, Article ID 521606, 12 pages
http://dx.doi.org/10.1155/2010/521606
Research Article

Application of Game Theory to Neuronal Networks

1School of Computing and Mathematics, Faculty of Computing and Engineering, University of Ulster, Shore Road, Newtownabbey, Co. Antrim BT37 0QB, Northern Ireland
2Laboratory for Dynamics of Emergent Intelligence, RIKEN Brain Science Institute, Wako-shi, Saitama 351-0198, Japan

Received 28 August 2009; Accepted 2 October 2009

Academic Editor: Naoyuki Sato

Copyright © 2010 Alfons Schuster and Yoko Yamaguchi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The paper is a theoretical investigation into the potential application of game theoretic concepts to neural networks (natural and artificial). The paper relies on basic models but the findings are more general in nature and therefore should apply to more complex environments. A major outcome of the paper is a learning algorithm based on game theory for a paired neuron system.