Abstract
Conversational interfaces have become a hot topic during the last years. Major research groups and technology companies have been making huge investments in research into technologies such as Artificial Intelligence, deep neural networks, machine learning, and natural language understanding with the aim of creating intelligent assistants that will enable users to interact with information and services in a natural, conversational way. However, most of the current conversational interfaces use hand-crafting dialog strategies and architectures tightly coupled to the application domain and are not adapted to the specific requirements and preferences of each user. In this paper, we propose a multi-agent architecture to develop user-adapted conversational interfaces. Our proposal considers two types of agents. Expert agents access different knowledge sources, and decision agents coordinate them to provide a coherent response to the user. We describe our proposal and its practical application to develop a conversational interface that provides bus schedule information.
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This work was supported in part by Projects TRA2015-63708-R and TRA2016-78886-C3-1-R.
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Griol, D., de Miguel, A.S., Molina, J.M. (2017). A Proposal to Enhance Human-Machine Interaction by Means of Multi-agent Conversational Interfaces. In: Martínez de Pisón, F., Urraca, R., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2017. Lecture Notes in Computer Science(), vol 10334. Springer, Cham. https://doi.org/10.1007/978-3-319-59650-1_48
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DOI: https://doi.org/10.1007/978-3-319-59650-1_48
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