@inproceedings { lobo21,
	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.},
	booktitle = {CONVERSATIONS'21 - the 5th International Workshop on Chatbot  Research},
	keywords = {Intelligent Virtual Agents;Miscellaneous;},
	month = {November},
	title = {Socially Aware Interactions: From Dialogue Trees to Natural Language Dialogue Systems},
	year = {2021},
	author = {Inês Lobo and Diogo Rato and Rui Prada and Frank Dignum}
}