Multiparty interactions for coordination in a mixed human-agent teamwork

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Abstract

Virtual environments for human learning enable one or more users to interact with virtual agents in order to perform their tasks. This collaboration necessitates that the members of the team share a set of beliefs and reason about resources, plans and actions to be implemented. This article introduces a new multiparty coordination model allowing several virtual and human agents to dialogue and reason about the tasks that the user must learn. The proposed model relies on a shared plan based approach to represent the beliefs of the team members. The management of the multiparty aspect makes it possible to differentiate the behaviors to be produced according to the type of receiver of a communication: recipient or listener. Finally, in the context of learning a procedural activity, a study examines the effect of our multiparty model on a learner. Results show that the use of proactive pedagogical agents with multiparty competencies boosts the construction of common beliefs.

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Barange, M., Saunier, J., & Pauchet, A. (2017). Multiparty interactions for coordination in a mixed human-agent teamwork. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10498 LNAI, pp. 29–42). Springer Verlag. https://doi.org/10.1007/978-3-319-67401-8_4

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