Agent-Based System for Context-Aware Human-Computer Interaction
Interaction between a human and a computer is a rapidly evolving field in computer science, with the goal to achieve efficient communication using natural language. In the recent couple of years, there have been significant accomplishments in the field, resulting with many commercially available systems capable of performing various tasks, while using natural language to communicate with human users. In this paper, we discuss the possibilities of extending the capabilities of such systems by adopting an agent-based approach. We present a model for a context-aware, intelligent, adaptive multi-agent system able to independently communicate with human users using natural language, i.e., speech. The motivation is to design an extensible system which could independently decide in which way to present information to the user, with the decision based on the user’s context, retrieved from any number of devices or systems. The focus of the paper will be on describing the interaction process itself, and the significance of context regarding the human-computer interaction.
KeywordsSoftware agent IoT Context-awareness Context resolution Human-computer interaction Natural language processing BDI Intelligent agent
This work has been supported in part by Croatian Regulatory Authority for Network Industries in scope of project “Looking to the Future”.
- 1.Rise of the Machines: How AI-Driven Personal Assistant Apps are Shaping Digital Consumer Habits. http://www.vertoanalytics.com. Accessed 08 Jan 2017
- 2.Soda, S., Nakamura, M., Matsumoto, S., Izumi, S., Kawaguchi H., Yoshimoto, M.: Implementing virtual agent as an interface for smart home voice control. In: 19th Asia-Pacific Software Engineering Conference, Hong Kong, pp. 342–345 (2012)Google Scholar
- 3.Raux, A., Langner, B.; Bohus, D., Black, A.W., Eskenazi, M.: Let’s go public! Taking a spoken dialog system to the real world. In: Proceedings of Interspeech, pp. 885–888 (2005)Google Scholar
- 4.The Rise of Intelligent Voice Assistants. http://www.wavestone.com. Accessed 05 Jan 2017
- 5.López, G., Quesada, L., Guerrero, L.A.: Alexa vs. Siri vs. Cortana vs. Google assistant: a comparison of speech-based natural user interfaces. In: Nunes, I. (ed.) Advances in Human Factors and Systems Interaction. AHFE 2017. Advances in Intelligent Systems and Computing, vol. 592, pp. 241–250. Springer, Cham (2018)Google Scholar
- 6.Lovrek, I.: Context awareness in mobile software agent network. RAD Croat. Acad. Sci. Arts. Tech. Sci. 513, 7–28 (2012)Google Scholar
- 9.Noguera-Arnaldos, J.Á., Paredes-Valverde, M.A., Salas-Zárate, M.P., Rodríguez-García, M.Á., Valencia-García, R., Ochoa, J.L.: im4Things: an ontology-based natural language interface for controlling devices in the Internet of Things. In: Alor-Hernández, G., Valencia-García, R. (eds.) Current Trends on Knowledge-Based Systems. Intelligent Systems Reference Library, vol. 120, pp. 3–22. Springer, Cham (2017)CrossRefGoogle Scholar
- 10.Gunasekera, K., Zaslavsky, A., Krishnaswamy, S., Loke, S.W.: Service oriented context-aware software agents for greater efficiency. In: Jędrzejowicz, P., Nguyen, N.T., Howlet, R.J., Jain, L.C. (eds.) Agent and Multi-Agent Systems: Technologies and Applications. KES-AMSTA 2010. LNCS, vol. 6070, pp. 62–71. Springer, Heidelberg (2010)CrossRefGoogle Scholar
- 11.Brézillon, P.: A context-centered architecture for intelligent assistant systems. In: Faucher, C., Jain, L. (eds.) Innovations in Intelligent Machines-4. Studies in Computational Intelligence, vol. 514. Springer, Cham (2014)Google Scholar