Personal assistant agents have been developed to help people in their daily lives with tasks such as agenda management. In order to provide better support, they should not only model the user’s internal aspects, but also their social situation. Current research on social context tackles this by modelling the social aspects of a situation from an objective perspective. In our approach, we model these social aspects of the situation from the user’s subjective perspective. We do so by using concepts from social science, and in turn apply machine learning techniques to predict the priority that the user would assign to these situations. Furthermore, we show that using these techniques allows agents to determine which features influenced these predictions. Results based on a crowd-sourcing user study suggest that our proposed model would enable personal assistant agents to differentiate between situations with high and low priority. We believe this to be a first step towards agents that better understand the user’s social situation, and adapt their support accordingly.
|Title of host publication||PRIMA 2020|
|Subtitle of host publication||Principles and Practice of Multi-Agent Systems - 23rd International Conference, 2020, Proceedings|
|Editors||Takahiro Uchiya, Quan Bai, Iván Marsá Maestre|
|Number of pages||17|
|Publication status||Published - 2021|
|Event||23rd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020 - Virtual, Online|
Duration: 18 Nov 2020 → 20 Nov 2020
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||23rd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020|
|Period||18/11/20 → 20/11/20|
Bibliographical noteGreen Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
- Adaptive personal assistants
- Explainable AI
- Machine learning techniques
- Social situations modelling
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