Responsive Social Agents: Feedback-Sensitive Behavior Generation for Social Interactions

Jered Hendrik Vroon; Gwenn Englebienne; Vanessa Evers

doi:10.1007/978-3-319-47437-3_13

Responsive Social Agents: Feedback-Sensitive Behavior Generation for Social Interactions

Jered Hendrik Vroon, Gwenn Englebienne, Vanessa Evers

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

4 Citations (Scopus)

155 Downloads (Pure)

Abstract

How can we generate appropriate behavior for social artificial agents? A common approach is to (1) establish with controlled experiments which action is most appropriate in which setting, and (2) select actions based on this knowledge and an estimate of the setting. This approach faces challenges, as it can be very hard to acquire and reason with all the required knowledge. Estimating the setting is challenging too, as many relevant aspects of the setting (e.g. personality of the interactee) can be unobservable. We formally describe an alternative approach that can handle these challenges; responsiveness. This is the idea that a social agent can utilize the many feedback cues given in social interactions to continuously adapt its behavior to something more appropriate. We theoretically discuss the relative advantages and disadvantages of these two approaches, which allows for more explicitly considering their application in social agents.

Original language	English
Title of host publication	Social Robotics
Subtitle of host publication	8th International Conference, ICSR 2016, Kansas City, MO, USA, November 1-3, 2016 Proceedings
Editors	Arvin Agah, John-John Cabibihan, Ayanna M. Howard, Miguel A. Salichs, Hongsheng He
Pages	126-137
Number of pages	12
ISBN (Electronic)	978-3-319-47437-3
DOIs	https://doi.org/10.1007/978-3-319-47437-3_13
Publication status	Published - Nov 2016
Event	8th International Conference on Social Robotics, ICSR 2016 - Kansas City, United States Duration: 1 Nov 2016 → 3 Nov 2016 Conference number: 8

Publication series

Name	Lecture notes in computer science
Volume	9979

Conference

Conference	8th International Conference on Social Robotics, ICSR 2016
Abbreviated title	ICSR 2016
Country/Territory	United States
City	Kansas City
Period	1/11/16 → 3/11/16

Keywords

Feedback
Control architectures
IR-104076
Social Robotics
EWI-27601

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10.1007/978-3-319-47437-3_13

Vroon2016_ICSR_CameraReady_ResponsiveSocialAgentsAccepted author version, 570 KB

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Vroon, J. H., Englebienne, G., & Evers, V. (2016). Responsive Social Agents: Feedback-Sensitive Behavior Generation for Social Interactions. In A. Agah, J.-J. Cabibihan, A. M. Howard, M. A. Salichs, & H. He (Eds.), Social Robotics: 8th International Conference, ICSR 2016, Kansas City, MO, USA, November 1-3, 2016 Proceedings (pp. 126-137). (Lecture notes in computer science; Vol. 9979). https://doi.org/10.1007/978-3-319-47437-3_13

Vroon, Jered Hendrik ; Englebienne, Gwenn ; Evers, Vanessa. / Responsive Social Agents: Feedback-Sensitive Behavior Generation for Social Interactions. Social Robotics: 8th International Conference, ICSR 2016, Kansas City, MO, USA, November 1-3, 2016 Proceedings. editor / Arvin Agah ; John-John Cabibihan ; Ayanna M. Howard ; Miguel A. Salichs ; Hongsheng He. 2016. pp. 126-137 (Lecture notes in computer science).

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abstract = "How can we generate appropriate behavior for social artificial agents? A common approach is to (1) establish with controlled experiments which action is most appropriate in which setting, and (2) select actions based on this knowledge and an estimate of the setting. This approach faces challenges, as it can be very hard to acquire and reason with all the required knowledge. Estimating the setting is challenging too, as many relevant aspects of the setting (e.g. personality of the interactee) can be unobservable. We formally describe an alternative approach that can handle these challenges; responsiveness. This is the idea that a social agent can utilize the many feedback cues given in social interactions to continuously adapt its behavior to something more appropriate. We theoretically discuss the relative advantages and disadvantages of these two approaches, which allows for more explicitly considering their application in social agents.",

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author = "Vroon, {Jered Hendrik} and Gwenn Englebienne and Vanessa Evers",

year = "2016",

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Vroon, JH, Englebienne, G & Evers, V 2016, Responsive Social Agents: Feedback-Sensitive Behavior Generation for Social Interactions. in A Agah, J-J Cabibihan, AM Howard, MA Salichs & H He (eds), Social Robotics: 8th International Conference, ICSR 2016, Kansas City, MO, USA, November 1-3, 2016 Proceedings. Lecture notes in computer science, vol. 9979, pp. 126-137, 8th International Conference on Social Robotics, ICSR 2016, Kansas City, Missouri, United States, 1/11/16. https://doi.org/10.1007/978-3-319-47437-3_13

Responsive Social Agents: Feedback-Sensitive Behavior Generation for Social Interactions. / Vroon, Jered Hendrik; Englebienne, Gwenn ; Evers, Vanessa.
Social Robotics: 8th International Conference, ICSR 2016, Kansas City, MO, USA, November 1-3, 2016 Proceedings. ed. / Arvin Agah; John-John Cabibihan; Ayanna M. Howard; Miguel A. Salichs; Hongsheng He. 2016. p. 126-137 (Lecture notes in computer science; Vol. 9979).

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

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AB - How can we generate appropriate behavior for social artificial agents? A common approach is to (1) establish with controlled experiments which action is most appropriate in which setting, and (2) select actions based on this knowledge and an estimate of the setting. This approach faces challenges, as it can be very hard to acquire and reason with all the required knowledge. Estimating the setting is challenging too, as many relevant aspects of the setting (e.g. personality of the interactee) can be unobservable. We formally describe an alternative approach that can handle these challenges; responsiveness. This is the idea that a social agent can utilize the many feedback cues given in social interactions to continuously adapt its behavior to something more appropriate. We theoretically discuss the relative advantages and disadvantages of these two approaches, which allows for more explicitly considering their application in social agents.

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T3 - Lecture notes in computer science

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A2 - Cabibihan, John-John

A2 - Howard, Ayanna M.

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Vroon JH, Englebienne G , Evers V. Responsive Social Agents: Feedback-Sensitive Behavior Generation for Social Interactions. In Agah A, Cabibihan JJ, Howard AM, Salichs MA, He H, editors, Social Robotics: 8th International Conference, ICSR 2016, Kansas City, MO, USA, November 1-3, 2016 Proceedings. 2016. p. 126-137. (Lecture notes in computer science). doi: 10.1007/978-3-319-47437-3_13

Responsive Social Agents: Feedback-Sensitive Behavior Generation for Social Interactions

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