Abstract
Based on the emotional model described by 3-dimensional state space, a complex emotional regulation model is proposed and applied to real-time dynamic emotional regulation process. Emotional stimulus (single basic emotional state stimulus or complex emotional state stimulus) is converted into a field source in the space by the vector calculation. So the potential scalar function of each point can be calculated and normalized to a transferring probability matrix of basic emotional states. Finally, the complex emotional state is produced by hidden Markov stimulus transferring model and an auxiliary matrix. The result shows that a complex emotional regulation model in active field gets rid of the simple emotional control mode and generates a kind of complex emotion. It is more in line with the demand of emotional regulation in a complex interactive environment.
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References
Wang, G., Teng, S., Fu, K.: Artificial Emotion Medel Based on Random Process. In: 2010 2nd International Workshop on Intelligent Systems and Applications (ISA), May 22-23, pp. 1–4 (2010)
Xu, Q.L., Zhou, F., Jiao, J.: Design for User Experience: an Affective-Cognitive Modeling Perspective. In: 2010 IEEE International Conference on Management of Innovation and Technolog (ICMIT), June 2-5, pp. 1019–1024 (2010)
Yu, D., Fang, J., Zhou, Y., Zhao, P.: A Model of Emotional Interactions Based on Affective Cognitive Algorithm. In: 11th International Conference on Advanced Communication Technology, ICACT 2009, Febuary 15-16, pp. 2149–2154 (2009)
Leon, E., Montalban, I., Schlatter, S., Dorronsoro, I.: Changes Using Non-Parametric Cumulative Sum. In: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), August 31-September 4, pp. 1109–1112 (2010)
Liu, X., Xie, L., Yang, W., Wang, Z., Fu, S.: Dynamic Regulation Process of Facial Expression Robot. Control Theory & Applications 28(7), 936–946 (2011)
Burgstaller, W., Lang, R., Porscht, P., Velik, R.: Technical Model for Basicc and Complex Emotions. In: 2007 5th IEEE International Conference on Industrial Informatics, June 23-27, pp. 1007–1012 (2007)
Breazeal, C.: Function Meets Style: Insights From Emotion Theory Applied to HRI. IEEE Transactions on Systems, Man, and Cybernetics-Part C: Applications and Reviews 34(2), 187–194 (2004)
Mstsumaru, T.: Discrimination of Emotion From movement and Addition of Emotion in Movement to Improve Human-Coexistence Robots Personal Affinity. In: Mstsumaru, T. (ed.) The 18th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2009, September 27-October 2, pp. 387–394 (2009)
EI-Nasr, M.S., Yen, Y.: Flame Fuzzy Logic Adaptive Model of Emotions. Autonomoius Agents and Muli-Agent Systems 3, 219–257 (2000)
Ji, S., Watson, L.T., Carin, L.: Flame Fuzzy Logic Adaptive Model of Emotions. Semisupervised Learning of Hidden Markov Models via a Homotopy Method 31(2), 275–287 (2009)
Wang, W., Wang, Z., Zheng, S., Gu, X.: Individual Differnence of Artificial Emotion Applied to a Service Robot. Frontiers of Computer Science in China 5(2), 216–226 (2011)
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Liu, X., Xie, L. (2013). Complex Emotional Regulation Process in Active Field State Space. In: Lee, S., Cho, H., Yoon, KJ., Lee, J. (eds) Intelligent Autonomous Systems 12. Advances in Intelligent Systems and Computing, vol 194. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33932-5_39
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DOI: https://doi.org/10.1007/978-3-642-33932-5_39
Publisher Name: Springer, Berlin, Heidelberg
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