Date: 16 Jan 2003

Extending the Computational Study of Social Norms with a Systematic Model of Emotions

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Abstract

It is generally recognized that the use of emotions plays an important role in human interactions, for it leads to more flexible decision-making. In the present work, we extend the idea presented in a paper by Castelfranchi, Conte, and Paolucci, by employing a systematic and detailed model of emotion generation. A scenario is described in which agents that have various types of emotions make decisions regarding compliance with a norm. We compare our results with the ones achieved in previous simulations and we show that the use of emotions leads to a selective behavior which increases agent performance, considering that different types of emotions cause agents to have different acting priorities.

Author partially supported by CNPq.