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DOI: http://dx.doi.org/10.7551/978-0-262-31709-2-ch122
Pages 830-837
First published 2 September 2013

EMANN - a model of emotions in an artificial neural network

Ronald Thenius, Payam Zahadat, Thomas Schmickl

Abstract

With the work at hand we want to present a model of a neural system, that is influenced by emotions. This model is based on the state of the art concept of artificial neural networks (ANN) which we improve by adding 'artificial emotions'. The way of the implementation of emotions is based on the research results regarding the biological and biochemical processes modulating neural cells in animals and humans. The described modulation takes place not only on the level of synapses, but also on the level of calculations happening on the membrane of the cell, or the node of the ANN, respectively. The suggested model also includes the biological fact, that neuro modulatory glands (e.g., hypophysis) are mainly controlled by the neuronal system itself. The resulting proposed system is named EMotional Artificial Neural Network (EMANN). It shows that EMANN has different abilities, compared to ANNs without emotions.