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Theory of Mind Assessment in Human-Robot Interaction
Conference proceeding   Peer reviewed

Theory of Mind Assessment in Human-Robot Interaction

L Marino, L D’Errico, Marco Matarese, A Cangelosi and M Staffa
16th International Conference, ICSR + AI 2024, Odense, Denmark, October 23–26, 2024, Proceedings, Part II, Vol.15562, pp.33-42
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 15562
International Conference on Social Robotics + AI (Naples, 10/09/2025–12/09/2025)
2025
Handle:
https://hdl.handle.net/10863/52119

Abstract

Human-Robot Interaction Socially Assistive Robotics Theory of mind Behavioral Programming False Belief Task
Theory of Mind (ToM) is a crucial inferential system in human communication, allowing individuals to attribute mental states to themselves and others, and predict behaviors based on these attributions. While it is probable that ToM plays a significant role in interactions with non-human agents displaying similar cues, it remains unclear if humans apply ToM to mechanical agents that exhibit intelligence and social characteristics. To address this gap, we designed an experimental setting to assess ToM in Human-Robot Interaction (HRI). This study investigates the influence of robots’ social attitude on users’ ToM and their performance in False Belief Tasks. We examine how the behavioral programming of robots affects human perceptions and the accuracy of verbal and non-verbal ToM assessments.
url
https://link.springer.com/chapter/10.1007/978-981-96-3519-1_4View

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