To Ask or Not to Ask: A User Annoyance Aware Preference Elicitation Framework for Social Robots

Balint Gucsi; Danesh S. Tarapore; William Yeoh; Christopher Amato; Long Tran-Thanh

IROS 2020poster6 citations

To Ask or Not to Ask: A User Annoyance Aware Preference Elicitation Framework for Social Robots

Balint Gucsi, Danesh S. Tarapore, William Yeoh, Christopher Amato, Long Tran-Thanh

Abstract

In this paper we investigate how social robots can efficiently gather user preferences without exceeding the allowed user annoyance threshold. To do so, we use a Gazebo based simulated office environment with a TIAGo Steel robot. We then formulate the user annoyance aware preference elicitation problem as a combination of tensor completion and knapsack problems. We then test our approach on the aforementioned simulated environment and demonstrate that it can accurately estimate user preferences.

BibTeX

@inproceedings{iros2020_toaskornottoaska,
  title = {To Ask or Not to Ask: A User Annoyance Aware Preference Elicitation Framework for Social Robots},
  author = {Balint Gucsi and Danesh S. Tarapore and William Yeoh and Christopher Amato and Long Tran-Thanh},
  booktitle = {IROS 2020},
  year = {2020}
}