Integrating Conversation Trees and Cognitive Models within an ECA for Aggression De-escalation Training.

T. Bosse; S. Provoost

doi:10.1007/978-3-319-25524-8_48

Integrating Conversation Trees and Cognitive Models within an ECA for Aggression De-escalation Training.

T. Bosse, S. Provoost

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Traditionally, Embodied Conversational Agents communicate with humans using dialogue systems based on conversation trees. To enhance the flexibility and variability of dialogues, this paper proposes an approach to integrate conversation trees with cognitive models. The approach is illustrated by a case study in the domain of aggression de-escalation training, and a preliminary evaluation in the context of a practical application is presented.

Original language	English
Title of host publication	PRIMA 2015: Principles and Practice of Multi-Agent Systems
Subtitle of host publication	18th International Conference Bertinoro, Italy, October 26 – 30, 2015 Proceedings
Editors	Q. Chen, P. Torroni, S. Villata, J. Hsu, A. Omicini
Publisher	Springer
Pages	650-659
Number of pages	10
ISBN (Electronic)	9783319255248
ISBN (Print)	9783319255231
DOIs	https://doi.org/10.1007/978-3-319-25524-8_48
Publication status	Published - 2015

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Verlag
Volume	9387
ISSN (Print)	0302-9743

Name	Lecture Notes in Artificial Intelligence
Volume	9387

Access to Document

10.1007/978-3-319-25524-8_48

Cite this

Bosse, T., & Provoost, S. (2015). Integrating Conversation Trees and Cognitive Models within an ECA for Aggression De-escalation Training. In Q. Chen, P. Torroni, S. Villata, J. Hsu, & A. Omicini (Eds.), PRIMA 2015: Principles and Practice of Multi-Agent Systems: 18th International Conference Bertinoro, Italy, October 26 – 30, 2015 Proceedings (pp. 650-659). (Lecture Notes in Computer Science; Vol. 9387), (Lecture Notes in Artificial Intelligence; Vol. 9387). Springer. https://doi.org/10.1007/978-3-319-25524-8_48

Bosse, T. ; Provoost, S. / Integrating Conversation Trees and Cognitive Models within an ECA for Aggression De-escalation Training. PRIMA 2015: Principles and Practice of Multi-Agent Systems: 18th International Conference Bertinoro, Italy, October 26 – 30, 2015 Proceedings. editor / Q. Chen ; P. Torroni ; S. Villata ; J. Hsu ; A. Omicini. Springer, 2015. pp. 650-659 (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence).

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author = "T. Bosse and S. Provoost",

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Bosse, T & Provoost, S 2015, Integrating Conversation Trees and Cognitive Models within an ECA for Aggression De-escalation Training. in Q Chen, P Torroni, S Villata, J Hsu & A Omicini (eds), PRIMA 2015: Principles and Practice of Multi-Agent Systems: 18th International Conference Bertinoro, Italy, October 26 – 30, 2015 Proceedings. Lecture Notes in Computer Science, vol. 9387, Lecture Notes in Artificial Intelligence, vol. 9387, Springer, pp. 650-659. https://doi.org/10.1007/978-3-319-25524-8_48

Integrating Conversation Trees and Cognitive Models within an ECA for Aggression De-escalation Training. / Bosse, T.; Provoost, S.

PRIMA 2015: Principles and Practice of Multi-Agent Systems: 18th International Conference Bertinoro, Italy, October 26 – 30, 2015 Proceedings. ed. / Q. Chen; P. Torroni; S. Villata; J. Hsu; A. Omicini. Springer, 2015. p. 650-659 (Lecture Notes in Computer Science; Vol. 9387), (Lecture Notes in Artificial Intelligence; Vol. 9387).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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Bosse T, Provoost S. Integrating Conversation Trees and Cognitive Models within an ECA for Aggression De-escalation Training. In Chen Q, Torroni P, Villata S, Hsu J, Omicini A, editors, PRIMA 2015: Principles and Practice of Multi-Agent Systems: 18th International Conference Bertinoro, Italy, October 26 – 30, 2015 Proceedings. Springer. 2015. p. 650-659. (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence). https://doi.org/10.1007/978-3-319-25524-8_48