Abstract
The modelling of the emotion regulation process is an important aspect that can contribute to the creation of more realistic intelligent virtual agents. The emotional reactions in a virtual agent, produced by the regulation process, can be useful to better adapt the agent’s behaviour to the particular requirements of a social interactive scenario. We propose a computational model of emotion regulation where the use of different strategies to down-regulate the negative emotions is based on personality-based individual differences. Our model implements a fuzzy mechanism that reproduce the correlation between different personality traits and the use of the specific emotion regulation strategies described in the literature. The validation of the model has been performed through a set of simulations where synthetic data have been generated to represent individuals with different personalities.
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The first author acknowledges the “Cátedras CONACyT” program funded by the Mexican National Research Council (CONACyT).
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Martínez-Miranda, J., Alvarado, M. (2017). Modelling Personality-Based Individual Differences in the Use of Emotion Regulation Strategies. In: Mouhoub, M., Langlais, P. (eds) Advances in Artificial Intelligence. Canadian AI 2017. Lecture Notes in Computer Science(), vol 10233. Springer, Cham. https://doi.org/10.1007/978-3-319-57351-9_41
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DOI: https://doi.org/10.1007/978-3-319-57351-9_41
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