This paper presents an experimental platform for studying intentional-state attribution toward a non-humanoid robot. The system combines a simulated robot, realistic task environments, and large language model-based explanatory layers that can express the same behavior in mentalistic, teleological, or mechanistic terms. By holding behavior constant while varying the explanatory frame, the platform provides a controlled way to investigate how language and framing shape the adoption of the intentional stance in robotics.
@article{arxiv.2603.25646,
title = {A Mentalistic Interface for Probing Folk-Psychological Attribution to Non-Humanoid Robots},
author = {Giulio Pisaneschi and Pierpaolo Serio and Estelle Gerbier and Andrea Dan Ryals and Lorenzo Pollini and Mario G. C. A. Cimino},
journal= {arXiv preprint arXiv:2603.25646},
year = {2026}
}