From psychological intention recognition theories to adaptive theory of mind for robots: Computational models

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Abstract

Progress in robots' application to everyday scenarios has increased the interest in human-robot interaction (HRI) research. However, robots' limited social skills are associated with decreased humans' positive attitude during HRI. Here, we put forward the idea of developing adaptive Theory of Mind (ToM) model-based systems for social robotics, able to deal with new situations and interact with different users in new tasks. Therefore, we grouped current research from developmental psychology debating the computational processes underlying ToM for HRI strategy development. Defining a model describing adaptive ToM processes may in fact aid the development of adaptive robotic architectures for more flexible and successful HRI. Finally, we hope with this report to both further promote the cross-talk between the fields of developmental psychology and robotics and inspire future investigations in this direction.

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Bianco, F., & Ognibene, Di. (2020). From psychological intention recognition theories to adaptive theory of mind for robots: Computational models. In ACM/IEEE International Conference on Human-Robot Interaction (pp. 136–138). IEEE Computer Society. https://doi.org/10.1145/3371382.3378364

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