Computational Mechanisms for Mental Models in Human-Robot Interaction

Author(s):  
Matthias Scheutz
2020 ◽  
Vol 12 (1) ◽  
pp. 58-73
Author(s):  
Sofia Thunberg ◽  
Tom Ziemke

AbstractInteraction between humans and robots will benefit if people have at least a rough mental model of what a robot knows about the world and what it plans to do. But how do we design human-robot interactions to facilitate this? Previous research has shown that one can change people’s mental models of robots by manipulating the robots’ physical appearance. However, this has mostly not been done in a user-centred way, i.e. without a focus on what users need and want. Starting from theories of how humans form and adapt mental models of others, we investigated how the participatory design method, PICTIVE, can be used to generate design ideas about how a humanoid robot could communicate. Five participants went through three phases based on eight scenarios from the state-of-the-art tasks in the RoboCup@Home social robotics competition. The results indicate that participatory design can be a suitable method to generate design concepts for robots’ communication in human-robot interaction.


Author(s):  
Matthew Rueben ◽  
Eitan Rothberg ◽  
Maja J. Matarić

People often make ascriptions that they believe to be literally false. A robot, for example, may be treated as if it were a dog, or as if it had certain intentions, emotions, or personality traits. How can one do this while also believing that robots cannot really have such traits? In this paper we explore how Kendall Walton’s theory of make-believe might account for this apparent paradox. We propose several extensions to Walton’s theory, some implications for how we make attributions and use mental models, and an informal account of human-robot interaction from the human’s perspective.


2009 ◽  
Author(s):  
Matthew S. Prewett ◽  
Kristin N. Saboe ◽  
Ryan C. Johnson ◽  
Michael D. Coovert ◽  
Linda R. Elliott

2010 ◽  
Author(s):  
Eleanore Edson ◽  
Judith Lytle ◽  
Thomas McKenna

2020 ◽  
Author(s):  
Agnieszka Wykowska ◽  
Jairo Pérez-Osorio ◽  
Stefan Kopp

This booklet is a collection of the position statements accepted for the HRI’20 conference workshop “Social Cognition for HRI: Exploring the relationship between mindreading and social attunement in human-robot interaction” (Wykowska, Perez-Osorio & Kopp, 2020). Unfortunately, due to the rapid unfolding of the novel coronavirus at the beginning of the present year, the conference and consequently our workshop, were canceled. On the light of these events, we decided to put together the positions statements accepted for the workshop. The contributions collected in these pages highlight the role of attribution of mental states to artificial agents in human-robot interaction, and precisely the quality and presence of social attunement mechanisms that are known to make human interaction smooth, efficient, and robust. These papers also accentuate the importance of the multidisciplinary approach to advance the understanding of the factors and the consequences of social interactions with artificial agents.


2019 ◽  
Author(s):  
Cinzia Di Dio ◽  
Federico Manzi ◽  
Giulia Peretti ◽  
Angelo Cangelosi ◽  
Paul L. Harris ◽  
...  

Studying trust within human-robot interaction is of great importance given the social relevance of robotic agents in a variety of contexts. We investigated the acquisition, loss and restoration of trust when preschool and school-age children played with either a human or a humanoid robot in-vivo. The relationship between trust and the quality of attachment relationships, Theory of Mind, and executive function skills was also investigated. No differences were found in children’s trust in the play-partner as a function of agency (human or robot). Nevertheless, 3-years-olds showed a trend toward trusting the human more than the robot, while 7-years-olds displayed the reverse behavioral pattern, thus highlighting the developing interplay between affective and cognitive correlates of trust.


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