Using emotions for the development of human-agent societies

[EN] Human-agent societies refer to applications where virtual agents and humans coexist and interact transparently into a fully integrated environment. One of the most important aspects in this kind of applications is including emotional states of the agents (humans or not) in the decision-making process. In this sense, this paper presents the applicability of the JaCalIVE framework for developing this kind of societies. Specifically, the paper presents an ambient intelligence application where humans are immersed into a system that extracts and analyzes the emotional state of a human group. A social emotional model is employed in order to try to maximize the welfare of those humans by playing the most appropriate music in every moment.Project supported by the Ministerio de Economia y Competitividad of the Spanish Government and the European Regional Development Fund of the European Union (No. TIN2015-65515-C4-1-R)Rincon, JA.; Bajo, J.; Fernandez, A.; Julian Inglada, VJ.; Carrascosa Casamayor, C. (2016). Using emotions for the development of human-agent societies. Frontiers of Information Technology & Electronic Engineering. 17(4):325-337. https://doi.org/10.1631/FITEE.1500343S325337174Ali, F., Amin, M., 2014. The influence of physical environment on emotions, customer satisfaction and behavioural intentions in Chinese resort hotel industry. J. Glob. Bus. Adv., 7(3):249–266. http://dx.doi.org/10.1504/JGBA.2014.064109Bales, R.F., 2001. Social Interaction Systems: Theory and Measurement. Transaction Publishers, USA.Barella, A., Ricci, A., Boissier, O., et al., 2012. MAM5: multi-agent model for intelligent virtual environments. Proc. 10th European Workshop on Multi-Agent Systems, p.16–30.Billhardt, H., Julian, V., Corchado, J.M., et al., 2014. An architecture proposal for human-agent societies. Proc. Int. Workshop on Highlights of Practical Applications of Heterogeneous Multi-Agent Systems, p.344–357. http://dx.doi.org/10.1007/978-3-319-07767-3_31Ducatel, K., Bogdanowicz, M., Scapolo, F., et al., 2001. Scenarios for Ambient Intelligence in 2010. Office for Official Publications of the European Communities.Fernandez, A., Ossowski, S., 2011. A multiagent approach to the dynamic enactment of semantic transportation services. IEEE Trans. Intell. Transp. Syst., 12(2):333–342. http://dx.doi.org/10.1109/TITS.2011.2106776Hale, K.S., Stanney, K.M., 2002. Handbook of Virtual Environments: Design, Implementation, and Applications. CRC Press, USA.Han, D.M., Lim, J.H., 2010. Smart home energy management system using IEEE 802.15.4 and ZigBee. IEEE Trans. Consum. Electron., 56(3):1403–1410. http://dx.doi.org/10.1109/TCE.2010.5606276Hendler, J., 2007. Where are all the intelligent agents? IEEE Intell. Syst., 22:2–3.Holzapfel, A., Stylianou, Y., 2007. A statistical approach to musical genre classification using non-negative matrix factorization. Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, p.693–696. http://dx.doi.org/10.1109/ICASSP.2007.366330Huhns, M.N., Singh, M.P., Burstein, M., et al., 2005. Research directions for service-oriented multiagent systems. IEEE Internet Comput., 9(6):65.Intille, S.S., 2002. Designing a home of the future. IEEE Perva. Comput., 1(2):76–82.Lawrence, S., Giles, C.L., Tsoi, A.C., et al., 1997. Face recognition: a convolutional neural-network approach. IEEE Trans. Neur. Netw., 8(1):98–113. http://dx.doi.org/10.1109/72.554195Li, T., Ogihara, M., Li, Q., 2003. A comparative study on content-based music genre classification. Proc. 26th Annual Int. ACM SIGIR Conf. on Research and Development in Information Retrieval, p.282–289. http://dx.doi.org/10.1145/860435.860487Mangina, E., Carbo, J., Molina, J.M., 2009. Agent-Based Ubiquitous Computing. Atlantis Press, France. http://dx.doi.org/10.2991/978-94-91216-31-2Mehrabian, A., 1980. Basic Dimensions for a General Psychological Theory: Implications for Personality, Social, Environmental, and Developmental Studies. Oelgeschlager, Gunn & Hain, USA.Mehrabian, A., 1997. Analysis of affiliation-related traits in terms of the PAD temperament model. J. Psychol., 131(1):101–117. http://dx.doi.org/10.1080/00223989709603508Nanty, A., Gelin, R., 2013. Fuzzy controlled PAD emotional state of a NAO robot. Proc. Conf. on Technologies and Applications of Artificial Intelligence, p.90–96. http://dx.doi.org/10.1109/TAAI.2013.30Ortony, A., 1990. The Cognitive Structure of Emotions. Cambridge University Press, USA.Ossowski, S., 2013. Agreement Technologies: 8 (Law, Governance and Technology Series). Springer, the Netherlands. http://dx.doi.org/10.1007/978-94-007-5583-3Osuna, E., Freund, R., Girosit, F., 1997. Training support vector machines: an application to face detection. Proc. IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, p.130–136. http://dx.doi.org/10.1109/CVPR.1997.609310Rincon, J.A., Garcia, E., Julian, V., et al., 2014. Developing adaptive agents situated in intelligent virtual environments. Proc. 9th Int. Conf. on Hybrid Artificial Intelligence Systems, p.98–109. http://dx.doi.org/10.1007/978-3-319-07617-1_9Rincon, J.A., Julian, V., Carrascosa, C., 2015a. Applying a social emotional model in human-agent societies. Proc. Int. Workshops of Practical Applications of Agents, Multi-Agent Systems, p.377–388. http://dx.doi.org/10.1007/978-3-319-19033-4_33Rincon, J.A., Julian, V., Carrascosa, C., 2015b. Social emotional model. Proc. 13th Int. Conf. on Practical Applications of Agents, Multi-Agent Systems, p.199–210. http://dx.doi.org/10.1007/978-3-319-18944-4_17Satyanarayanan, M., 2001. Pervasive computing: vision and challenges. IEEE Pers. Commun., 8(4):10–17. http://dx.doi.org/10.1109/98.943998Satyanarayanan, M., 2002. A catalyst for mobile and ubiquitous computing. IEEE Perva. Comput., 1(1):2–5. http://dx.doi.org/10.1109/MPRV.2002.993138Talupur, M., Nath, S., Yan, H., 2001. Classification of Music Genre. Project Report for 15781.Viola, P., Jones, M.J., 2004. Robust real-time face detection. Int. J. Comput. Vis., 57(2):137–154. http://dx.doi.org/10.1023/B:VISI.0000013087.49260.fbWeiser, M., 1991. The computer for the 21st century. Sci. Am., 265(3):94–104. http://dx.doi.org/10.1038/scientificamerican0991-94Zambonelli, F., Jennings, N.R., Wooldridge, M., 2003. Developing multiagent systems: the Gaia methodology. ACM Trans. Softw. Eng. Meth., 12(3):317–370. http://dx.doi.org/10.1145/958961.95896