@inproceedings {pub6136,
	title = {Quantifying and Reducing Mental Model Mismatch for Cooperative Robot Teaching},
	author = {Phillip Richter AND Heiko Wersing AND Anna-Lisa Vollmer},
	year = {2025},
	month = {March},
	abstract = {A major challenge in human-robot interaction (HRI) is the mental model mismatch, which arises when a human{\textquoteright}s understanding of a robot{\textquoteright}s capabilities differs from the robot{\textquoteright}s actual operational model. Such mismatches can result in ineffective teaching, suboptimal performance, and interaction breakdowns. This project aims to quantify mental model mismatch by formalizing and comparing human expectations with robot learning processes, enabling a structured approach to improving teaching efficiency. By providing tailored feedback and enhancing transparency in the teaching process, the ultimate goal is to empower humans to form realistic expectations about robots and optimize instructional strategies. The vision is to foster intuitive and effective cooperative learning, where humans and robots collaborate seamlessly, leading to improved task execution and generalization capabilities across various scenarios.},
	publisher = {Robotics Institute Germany},
	booktitle = {1st German Robotics Conference (GRC)}
}