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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Notes
- 1.
Even when limiting ourselves to ‘just’ the relevant setting variables (\(V^{R}\)) this would already be \(\prod _{v{'}\in V^{R}} \left| D_{v{'}}\right| \) combinations (since \(\left| D_{v{'}}\right| \ge 2\) for all meaningful variables, this is at least \(2^{\left| V^{R}\right| }\)).
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Acknowledgements
The work described in this paper has partly been supported by the European Commission under contract number FP7-ICT-611153 (TERESA).
We are grateful for the critical and open-minded comments of Khiet Truong, Dennis Reidsma, Daniel Davison, Bob Schadenberg, Jan Kolkmeier, Michiel Joosse, Roelof de Vries, Jorge Gallego Pérez, Jeroen Linssen and Dirk Heylen.
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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. https://doi.org/10.1007/978-3-319-47437-3_13
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DOI: https://doi.org/10.1007/978-3-319-47437-3_13
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