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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bickmore, T., Gruber, A.: Relational agents in clinical psychiatry. Harv. Rev. Psychiatry 18(2), 119–130 (2010)
Gross, J.J., Thompson, R.A.: Emotion regulation: conceptual foundations. In: Gross, J.J. (ed.) Handbook of Emotion Regulation, pp. 3–24. The Guilford Press, New York (2007)
John, O.P., Gross, J.J.: Individual differences in emotion regulation. In: Gross, J.J. (ed.) Handbook of Emotion Regulation, pp. 351–372. The Guilford Press, New York (2007)
John, O.P., Eng, J.: Three approaches to individual differences in affect regulation: conceptualizations, measures, and findings. In: Gross, J.J. (ed.) Handbook of Emotion Regulation, 2nd edn, pp. 321–345. The Guilford Press, New York (2015)
Marsella, S., Gratch, J., Petta, P.: Computational models of emotion. In: Scherer, K.R., Bänziger, T., Roesch, E.B. (eds.) Blueprint for Affective Computing: A Sourcebook, pp. 21–46. Oxford University Press, Oxford (2010)
Rothbart, M.K., Sheese, B.E.: Temperament and emotion regulation. In: Gross, J.J. (ed.) Handbook of Emotion Regulation, pp. 331–350. The Guilford Press, New York (2007)
Campos, J.J., Frankel, C.B., Camras, L.: On the nature of emotion regulation. Child Dev. 75, 377–394 (2004)
Frijda, N.H.: The Emotions. Cambridge University Press, Cambridge (1986)
Davidson, R.J., Fox, A., Kalin, N.H.: Neural bases of emotion regulation in nonhuman primates and humans. In: Gross, J.J. (ed.) Handbook of Emotion Regulation, pp. 47–68. The Guilford Press, New York (2007)
Gross, J.J., John, O.P.: Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being. J. Pers. Soc. Psychol. 85, 348–362 (2003)
Abler, B., Kessler, H.: Emotion regulation questionnaire: a German version of the ERQ by Gross and John. Diagnostica 55, 144–152 (2009)
Balzarotti, S., John, O.P., Gross, J.J.: An Italian adaptation of the emotion regulation questionnaire. Eur. J. Psychol. Assess 26, 61–67 (2010)
English, T., John, O.P.: Understanding the social effects of emotion regulation: the mediating role of authenticity for individual differences in suppression. Emotion 13, 314–329 (2013)
Gratch, J., Marsella, S.: A domain-independent framework for modeling emotion. J. Cogn. Syst. Res. 5(4), 269–306 (2004)
Lazarus, R.: Emotion and Adaptation. Oxford University Press, Oxford (1991)
Gratch, J., Marsella, S.: Modeling coping behavior in virtual humans: don’t worry, be happy. In: Proceedings of the 2nd International Joint Conference on Autonomous Agents and Multiagent Systems (2003)
Bosse, T., Pontier, M., Treur, J.: A computational model based on Gross’ emotion regulation theory. Cogn. Syst. Res. 11, 211–230 (2010)
Soleimain, A., Kobti, Z.: A fuzzy logic computational model for emotion regulation based on gross theory. In: Proceedings of the 26th International Florida Artificial Intelligence Research Society Conference (2013)
Manzoor, A., Abro, A.H., Treur, J.: Monitoring the impact of negative events and deciding about emotion regulation strategies. In: Proceedings of the 14th European Conference on Multi-Agent Systems (2016)
Martínez-Miranda, J., Bresó, A., García-Gómez, J.M.: Modelling two emotion regulation strategies as key features of therapeutic empathy. In: Bosse, T., et al. (eds.) Emotion Modeling: Towards Pragmatic Computational Models of Affective Processes, 115–133. Springer International Publishing, Cham (2014)
John, O.P.: The “Big Five” factor taxonomy: dimensions of personality in the natural language and in questionnaires. In: Pervin, L.A. (ed.) Handbook of Personality: Theory and Research, pp. 66–100. Guilford Press, New York (1990)
Cingolani, P., Alcalá-Fdez, J.: jFuzzyLogic: a robust and flexible Fuzzy-Logic inference system language implementation. In: Proceedings of IEEE International Conference on Fuzzy Systems, pp. 1–8 (2012)
Mamdani, E.H., Assilian, S.: An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Man Mach. Stud. 7(1), 1–13 (1975)
Acknowledgements
The first author acknowledges the “Cátedras CONACyT” program funded by the Mexican National Research Council (CONACyT).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-319-57351-9_41
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-57350-2
Online ISBN: 978-3-319-57351-9
eBook Packages: Computer ScienceComputer Science (R0)