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.
CITATION STYLE
Schuster, A., & Yamaguchi, Y. (2010). Application of Game Theory to Neuronal Networks. Advances in Artificial Intelligence, 2010, 1–12. https://doi.org/10.1155/2010/521606
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