abstract

From Psychological Intention Recognition Theories to Adaptive Theory of Mind for Robots: Computational Models

Authors:

Francesca Bianco,

Dimitri OgnibeneAuthors Info & Claims

HRI '20: Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction

Pages 136 - 138

https://doi.org/10.1145/3371382.3378364

Published: 01 April 2020 Publication History

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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Cited By

Wei DChen LZhao LZhou HHuang B(2022)A Vision-Based Measure of Environmental Effects on Inferring Human Intention During Human Robot InteractionIEEE Sensors Journal10.1109/JSEN.2021.313959322:5(4246-4256)Online publication date: 1-Mar-2022
https://doi.org/10.1109/JSEN.2021.3139593
Lindblom JAlenljung B(2020)The ANEMONE: Theoretical Foundations for UX Evaluation of Action and Intention Recognition in Human-Robot InteractionSensors10.3390/s2015428420:15(4284)Online publication date: 31-Jul-2020
https://doi.org/10.3390/s20154284

Index Terms

From Psychological Intention Recognition Theories to Adaptive Theory of Mind for Robots: Computational Models
1. Computing methodologies
  1. Artificial intelligence
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Collaborative interaction

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Published In

cover image ACM Conferences

HRI '20: Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction

March 2020

702 pages

ISBN:9781450370578

DOI:10.1145/3371382

General Chairs:
Tony Belpaeme
Ghent University, Belgium
,
James Young
University of Manitoba, Canada
,
Program Chairs:
Hatice Gunes
University of Cambridge, UK
,
Laurel Riek
UC San Diego, USA

Copyright © 2020 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 01 April 2020

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HRI '20

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HRI '20: ACM/IEEE International Conference on Human-Robot Interaction

March 23 - 26, 2020

Cambridge, United Kingdom

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Cited By

Wei DChen LZhao LZhou HHuang B(2022)A Vision-Based Measure of Environmental Effects on Inferring Human Intention During Human Robot InteractionIEEE Sensors Journal10.1109/JSEN.2021.313959322:5(4246-4256)Online publication date: 1-Mar-2022
https://doi.org/10.1109/JSEN.2021.3139593
Lindblom JAlenljung B(2020)The ANEMONE: Theoretical Foundations for UX Evaluation of Action and Intention Recognition in Human-Robot InteractionSensors10.3390/s2015428420:15(4284)Online publication date: 31-Jul-2020
https://doi.org/10.3390/s20154284

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