scholarly journals Communication Models in Human–Robot Interaction: An Asymmetric MODel of ALterity in Human–Robot Interaction (AMODAL-HRI)

2021 ◽  
Author(s):  
Helena Anna Frijns ◽  
Oliver Schürer ◽  
Sabine Theresia Koeszegi
Keyword(s):  
Interpersonal Communication ◽  
Joint Action ◽  
Communication Theory ◽  
Interaction Model ◽  
Interdisciplinary Approach ◽  
Human Robot Interaction ◽  
Cognitive Architectures ◽  
Robot Interaction ◽  
Asymmetric Model ◽  
Communication Models

AbstractWe argue for an interdisciplinary approach that connects existing models and theories in Human–Robot Interaction (HRI) to traditions in communication theory. In this article, we review existing models of interpersonal communication and interaction models that have been applied and developed in the contexts of HRI and social robotics. We argue that often, symmetric models are proposed in which the human and robot agents are depicted as having similar ways of functioning (similar capabilities, components, processes). However, we argue that models of human–robot interaction or communication should be asymmetric instead. We propose an asymmetric interaction model called AMODAL-HRI (an Asymmetric MODel of ALterity in Human–Robot Interaction). This model is based on theory on joint action, common robot architectures and cognitive architectures, and Kincaid’s model of communication. On the basis of this model, we discuss key differences between humans and robots that influence human expectations regarding interacting with robots, and identify design implications.

scholarly journals Neuro-cognitive mechanisms of decision making in joint action: A human–robot interaction study

2011 ◽  
Vol 30 (5) ◽  
pp. 846-868 ◽  
Author(s):  
Estela Bicho ◽  
Wolfram Erlhagen ◽  
Luis Louro ◽  
Eliana Costa e Silva
Keyword(s):  
Decision Making ◽  
Joint Action ◽  
Human Robot Interaction ◽  
Interaction Study ◽  
Cognitive Mechanisms ◽  
Robot Interaction

Of Mental States and Machine Learning

2016 ◽  
Vol 60 (1) ◽  
pp. 1362-1366 ◽  
Author(s):  
Andrew Best ◽  
Samantha F. Warta ◽  
Katelynn A. Kapalo ◽  
Stephen M. Fiore
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Social Cognition ◽  
Mental State ◽  
Response Times ◽  
Interdisciplinary Approach ◽  
Mental States ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Machine Learning Classifiers

Using research in social cognition as a foundation, we studied rapid versus reflective mental state attributions and the degree to which machine learning classifiers can be trained to make such judgments. We observed differences in response times between conditions, but did not find significant differences in the accuracy of mental state attributions. We additionally demonstrate how to train machine classifiers to identify mental states. We discuss advantages of using an interdisciplinary approach to understand and improve human-robot interaction and to further the development of social cognition in artificial intelligence.

Joint Action in Humans: A Model for Human-Robot Interaction

2018 ◽  
pp. 2149-2167 ◽  
Author(s):  
Arianna Curioni ◽  
Gunther Knoblich ◽  
Natalie Sebanz
Keyword(s):  
Joint Action ◽  
Human Robot Interaction ◽  
Robot Interaction

EXTENDING FEYNMAN'S FORMALISMS FOR MODELING HUMAN JOINT ACTION COORDINATION

2009 ◽  
Vol 02 (01) ◽  
pp. 1-7 ◽  
Author(s):  
VLADIMIR G. IVANCEVIC ◽  
EUGENE V. AIDMAN ◽  
LEONG YEN
Keyword(s):  
Joint Action ◽  
Human Action ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Infinite Dimensional ◽  
Proposed Model ◽  
Potential Applications ◽  
Individual Actor ◽  
Human Motor ◽  
Interaction Research

The recently developed Life-Space-Foam approach to goal-directed human action deals with individual actor dynamics. This paper applies the model to characterize the dynamics of co-action by two or more actors. This dynamics is modelled by (i) a two-term joint action (including cognitive/motivatonal potential and kinetic energy), and (ii) its associated adaptive path integral, representing an infinite-dimensional neural network. Its feedback adaptation loop has been derived from Bernstein's concepts of sensory corrections loop in human motor control and Brooks' subsumption architectures in robotics. Potential applications of the proposed model in human-robot interaction research are discussed.

MIHR: A Human-Robot Interaction Model

2020 ◽  
Vol 18 (09) ◽  
pp. 1521-1529
Author(s):  
Jesus Perez ◽  
Jose Aguilar ◽  
Eladio Dapena
Keyword(s):  
Interaction Model ◽  
Human Robot Interaction ◽  
Robot Interaction

scholarly journals The perception of a robot partner’s effort elicits a sense of commitment to human-robot interaction

2019 ◽  
Vol 20 (2) ◽  
pp. 234-255
Author(s):  
Marcell Székely ◽  
Henry Powell ◽  
Fabio Vannucci ◽  
Francesco Rea ◽  
Alessandra Sciutti ◽  
...  
Keyword(s):  
Joint Action ◽  
Humanoid Robot ◽  
Human Robot Interaction ◽  
Robot Interaction

Abstract Previous research has shown that the perception that one’s partner is investing effort in a joint action can generate a sense of commitment, leading participants to persist longer despite increasing boredom. The current research extends this finding to human-robot interaction. We implemented a 2-player version of the classic snake game which became increasingly boring over the course of each round, and operationalized commitment in terms of how long participants persisted before pressing a ‘finish’ button to conclude each round. Participants were informed that they would be linked via internet with their partner, a humanoid robot. Our results reveal that participants persisted longer when they perceived what they believed to be cues of their robot partner’s effortful contribution to the joint action. This provides evidence that the perception of a robot partner’s effort can elicit a sense of commitment to human-robot interaction.

scholarly journals A Survey of Behavioural Models for Social Robots

2019 ◽  
Author(s):  
Olivia Nocentini ◽  
Laura Fiorini ◽  
Giorgia Acerbi ◽  
Alessandra Sorrentino ◽  
Gianmaria Mancioppi ◽  
...  
Keyword(s):  
Web Of Science ◽  
Social Robots ◽  
Human Robot Interaction ◽  
Cognitive Architectures ◽  
Robot Interaction ◽  
Exclusion Criteria ◽  
Pros And Cons

The cooperation between humans and robots is becoming increasingly important in our society. Consequently, there is a growing interest in the development of models that can enhance the interaction between humans and robots. A key challenge in the Human-Robot Interaction (HRI) field is to provide robots with cognitive and affective capabilities, developing architectures that let them establish empathetic relationships with users. Several models have been proposed in recent years to solve this open-challenge. This work provides a survey of the most relevant attempts/works. In details, it offers an overview of the architectures present in literature focusing on three specific aspects of HRI: the development of adaptive behavioural models, the design of cognitive architectures, and the ability to establish empathy with the user. The research was conducted within two databases: Scopus and Web of Science. Accurate exclusion criteria were applied to screen the 1007 articles found (at the end 30 articles were selected). For each work, an evaluation of the model is made. Pros and cons of each work are detailed by analysing the aspects that can be improved so that an enjoyable interaction between robots and users can be established.

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