Abstract
In this paper, we present a prototype of a human-agent dialogue system, in which the scenarios are easy-to-author, as in tree-based dialogue tools. These, however, only allow for scripted and restricted dialogues. For this reason, we focused on developing a flexible and robust deliberation mechanism as well, based on the Cognitive Social Frames model and the theory of social practices, so that the conversational agent could provide acceptable responses according to different social contexts. Having access to sequences of frames containing small dialogue trees, the agent activates the most salient frame to reply appropriately to the user’s input. As a proof of concept, we designed a medical diagnosis scenario between a doctor and a patient in which the agent could play both roles given different settings of the scenario. In this prototype, the user had to choose from a limited set of alternatives, based on the current context, in order to respond to the agent; however, in the future, we intend to allow users to write freely, expecting to be able to map their utterances to the appropriate context.
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Acknowledgement(s)
The presented work was funded by the European Commission as part of the Humane-AI-net project, under grant agreement number 952026. It was supported by national funds through Fundação para a Ciência e a Tecnologia (FCT) with reference UIDB/50021/2020. Diogo Rato acknowledges his FCT grant (SFRH BD/131024/2017).
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Lobo, I., Rato, D., Prada, R., Dignum, F. (2022). Socially Aware Interactions: From Dialogue Trees to Natural Language Dialogue Systems. In: Følstad, A., et al. Chatbot Research and Design. CONVERSATIONS 2021. Lecture Notes in Computer Science(), vol 13171. Springer, Cham. https://doi.org/10.1007/978-3-030-94890-0_8
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