Balint Gucsi — accepted AI-conference papers

2025

User-Aware Collaborative Learning in Human-Robot Interactions

Balint Gucsi, Nguyen Tan Viet Tuyen, Bing Chu, Danesh S. Tarapore, Long Tran-Thanh

ICRA 2025

Our work investigates how social robots can efficiently collaborate with human users in a user-aware manner, minimising the generated frustration in human colleagues, thus enhancing their experience. As part of this, we develop a useraware framework for human-robot collaborative learning. We model u

Cited by 0 Source ↗Scholar ↗

2020

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 2020poster

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 prob…

Cited by 6 Source ↗Scholar ↗