Abstract
This paper addresses a collective decision model based on interacting adaptive agents that learn from their experiences by a Hebbian learning mechanism. The decision making process makes use of emotion-related valuing of decision options on the one hand based on predictive loops through feeling states, and on the other hand based on contagion. The resulting collective decision making process is analysed from the perspective of learning speed and rationality. It is shown how the collectiveness amplifies both learning speed and rationality of the decisions.
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Bosse, T., Treur, J., Umair, M. (2012). Rationality for Adaptive Collective Decision Making Based on Emotion-Related Valuing and Contagion. In: Ding, W., Jiang, H., Ali, M., Li, M. (eds) Modern Advances in Intelligent Systems and Tools. Studies in Computational Intelligence, vol 431. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30732-4_13
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DOI: https://doi.org/10.1007/978-3-642-30732-4_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30731-7
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