Responsive Social Agents

Feedback-Sensitive Behavior Generation for Social Interactions
Conference paper

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

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9979)
Cite this paper as:
Vroon J., Englebienne G., Evers V. (2016) Responsive Social Agents. In: Agah A., Cabibihan JJ., Howard A., Salichs M., He H. (eds) Social Robotics. ICSR 2016. Lecture Notes in Computer Science, vol 9979. Springer, Cham


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.


Control architectures Social robotics Feedback 

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Human Media InteractionUniversity of TwenteEnschedeThe Netherlands

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