Bianco, Francesca and Ognibene, Dimitri (2020) From Psychological Intention Recognition Theories to Adaptive Theory of Mind for Robots. In: HRI '20: ACM/IEEE International Conference on Human-Robot Interaction, 2020-03 - 2020-03, Cambridge, UK.
Bianco, Francesca and Ognibene, Dimitri (2020) From Psychological Intention Recognition Theories to Adaptive Theory of Mind for Robots. In: HRI '20: ACM/IEEE International Conference on Human-Robot Interaction, 2020-03 - 2020-03, Cambridge, UK.
Bianco, Francesca and Ognibene, Dimitri (2020) From Psychological Intention Recognition Theories to Adaptive Theory of Mind for Robots. In: HRI '20: ACM/IEEE International Conference on Human-Robot Interaction, 2020-03 - 2020-03, Cambridge, UK.
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.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Published proceedings: Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction |
Uncontrolled Keywords: | Theory of Mind; Intention Recognition; Belief Recognition; Action recognition; Prediction; User state |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 24 Apr 2020 15:34 |
Last Modified: | 01 Nov 2024 17:14 |
URI: | http://repository.essex.ac.uk/id/eprint/27365 |
Available files
Filename: 3371382.3378364.pdf