Kaspar Causally Explains

Hugo Araujo; Patrick Holthaus; Marina Sarda Gou; Gabriella Lakatos; Giulia  Galizia; Luke Wood; Ben Robins; Mohammadreza Mousavi; Farshid Amirabdollahian

doi:10.1007/978-3-031-24670-8_9

Kaspar Causally Explains

Hugo Araujo, Patrick Holthaus, Marina Sarda Gou, Gabriella Lakatos, Giulia Galizia, Luke Wood, Ben Robins, Mohammadreza Mousavi, Farshid Amirabdollahian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

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Abstract

The Kaspar robot has been used with great success to work as an education and social mediator with children with autism spectrum disorder. Enabling the robot to automatically generate causal explanations is key to enrich the interaction scenarios for children and promote trust in the robot. We present a theory of causal explanation to be embedded in Kaspar. Based on this theory, we build a causal model and an analysis method to calculate causal explanations. We implement our method in Java with inputs provided by a human operator. This model automatically generates the causal explanation that are then spoken by Kaspar. We validate our explanations for user satisfaction in an empirical evaluation.

Original language	English
Title of host publication	Social Robotics
Subtitle of host publication	Proceedings of 14thInternational Conference on Social Robotics, ICSR 2022, Part II
Editors	Filippo Cavallo, John-John Cabibihan, Laura Fiorini, Alessandra Sorrentino, Hongsheng He, Xiaorui Liu, Yoshio Matsumoto, Shuzhi Sam Ge
Place of Publication	Florence, Italy
Publisher	Springer Nature
Chapter	Contents – Part II
Pages	85-99
Number of pages	15
Volume	LNAI 13818
ISBN (Electronic)	978-3-031-24670-8
ISBN (Print)	978-3-031-24669-2
DOIs	https://doi.org/10.1007/978-3-031-24670-8_9
Publication status	Published - 2 Feb 2023
Event	14th International Conference on Social Robotics - Florence, Italy Duration: 13 Dec 2022 → 16 Dec 2022 https://www.icsr2022.it/

Publication series

Name	Lecture Notes in Computer Science

Conference

Conference	14th International Conference on Social Robotics
Abbreviated title	ICSR
Country/Territory	Italy
City	Florence
Period	13/12/22 → 16/12/22
Internet address	https://www.icsr2022.it/

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kaspar
© 2022 The Editor(s) and The Author(s), under exclusive license to Springer Nature Switzerland AG. This is the accepted manuscript version of a conference paper that has been published in final form at https://doi.org/10.1007/978-3-031-24670-8
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Araujo, H., Holthaus, P., Sarda Gou, M., Lakatos, G., Galizia, G., Wood, L., Robins, B., Mousavi, M., & Amirabdollahian, F. (2023). Kaspar Causally Explains. In F. Cavallo, J.-J. Cabibihan, L. Fiorini, A. Sorrentino, H. He, X. Liu, Y. Matsumoto, & S. S. Ge (Eds.), Social Robotics: Proceedings of 14thInternational Conference on Social Robotics, ICSR 2022, Part II (Vol. LNAI 13818, pp. 85-99). (Lecture Notes in Computer Science). Springer Nature . https://doi.org/10.1007/978-3-031-24670-8_9

Araujo, Hugo ; Holthaus, Patrick ; Sarda Gou, Marina et al. / Kaspar Causally Explains. Social Robotics: Proceedings of 14thInternational Conference on Social Robotics, ICSR 2022, Part II. editor / Filippo Cavallo ; John-John Cabibihan ; Laura Fiorini ; Alessandra Sorrentino ; Hongsheng He ; Xiaorui Liu ; Yoshio Matsumoto ; Shuzhi Sam Ge. Vol. LNAI 13818 Florence, Italy : Springer Nature , 2023. pp. 85-99 (Lecture Notes in Computer Science).

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abstract = "The Kaspar robot has been used with great success to work as an education and social mediator with children with autism spectrum disorder. Enabling the robot to automatically generate causal explanations is key to enrich the interaction scenarios for children and promote trust in the robot. We present a theory of causal explanation to be embedded in Kaspar. Based on this theory, we build a causal model and an analysis method to calculate causal explanations. We implement our method in Java with inputs provided by a human operator. This model automatically generates the causal explanation that are then spoken by Kaspar. We validate our explanations for user satisfaction in an empirical evaluation.",

author = "Hugo Araujo and Patrick Holthaus and {Sarda Gou}, Marina and Gabriella Lakatos and Giulia Galizia and Luke Wood and Ben Robins and Mohammadreza Mousavi and Farshid Amirabdollahian",

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Araujo, H, Holthaus, P, Sarda Gou, M, Lakatos, G, Galizia, G, Wood, L , Robins, B, Mousavi, M & Amirabdollahian, F 2023, Kaspar Causally Explains. in F Cavallo, J-J Cabibihan, L Fiorini, A Sorrentino, H He, X Liu, Y Matsumoto & SS Ge (eds), Social Robotics: Proceedings of 14thInternational Conference on Social Robotics, ICSR 2022, Part II. vol. LNAI 13818, Lecture Notes in Computer Science, Springer Nature , Florence, Italy, pp. 85-99, 14th International Conference on Social Robotics, Florence, Italy, 13/12/22. https://doi.org/10.1007/978-3-031-24670-8_9

Kaspar Causally Explains. / Araujo, Hugo; Holthaus, Patrick; Sarda Gou, Marina et al.
Social Robotics: Proceedings of 14thInternational Conference on Social Robotics, ICSR 2022, Part II. ed. / Filippo Cavallo; John-John Cabibihan; Laura Fiorini; Alessandra Sorrentino; Hongsheng He; Xiaorui Liu; Yoshio Matsumoto; Shuzhi Sam Ge. Vol. LNAI 13818 Florence, Italy: Springer Nature , 2023. p. 85-99 (Lecture Notes in Computer Science).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Kaspar Causally Explains

AU - Araujo, Hugo

AU - Holthaus, Patrick

AU - Sarda Gou, Marina

AU - Lakatos, Gabriella

AU - Galizia, Giulia

AU - Wood, Luke

AU - Robins, Ben

AU - Mousavi, Mohammadreza

AU - Amirabdollahian, Farshid

N1 - © 2022 The Editor(s) and The Author(s), under exclusive license to Springer Nature Switzerland AG. This is the accepted manuscript version of a conference paper that has been published in final form at https://doi.org/10.1007/978-3-031-24670-8

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N2 - The Kaspar robot has been used with great success to work as an education and social mediator with children with autism spectrum disorder. Enabling the robot to automatically generate causal explanations is key to enrich the interaction scenarios for children and promote trust in the robot. We present a theory of causal explanation to be embedded in Kaspar. Based on this theory, we build a causal model and an analysis method to calculate causal explanations. We implement our method in Java with inputs provided by a human operator. This model automatically generates the causal explanation that are then spoken by Kaspar. We validate our explanations for user satisfaction in an empirical evaluation.

AB - The Kaspar robot has been used with great success to work as an education and social mediator with children with autism spectrum disorder. Enabling the robot to automatically generate causal explanations is key to enrich the interaction scenarios for children and promote trust in the robot. We present a theory of causal explanation to be embedded in Kaspar. Based on this theory, we build a causal model and an analysis method to calculate causal explanations. We implement our method in Java with inputs provided by a human operator. This model automatically generates the causal explanation that are then spoken by Kaspar. We validate our explanations for user satisfaction in an empirical evaluation.

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A2 - Cavallo, Filippo

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A2 - Matsumoto, Yoshio

A2 - Ge, Shuzhi Sam

PB - Springer Nature

CY - Florence, Italy

T2 - 14th International Conference on Social Robotics

Y2 - 13 December 2022 through 16 December 2022

ER -

Araujo H, Holthaus P, Sarda Gou M, Lakatos G, Galizia G, Wood L et al. Kaspar Causally Explains. In Cavallo F, Cabibihan JJ, Fiorini L, Sorrentino A, He H, Liu X, Matsumoto Y, Ge SS, editors, Social Robotics: Proceedings of 14thInternational Conference on Social Robotics, ICSR 2022, Part II. Vol. LNAI 13818. Florence, Italy: Springer Nature . 2023. p. 85-99. (Lecture Notes in Computer Science). Epub 2023 Feb 2. doi: 10.1007/978-3-031-24670-8_9

Kaspar Causally Explains

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