Paper Info
Title
Pragmatic Frames for Teaching and Learning in Human-Robot Interaction: Review and Challenges.
Abstract
One of the big challenges in robotics today is to learn from human users that are inexperienced in interacting with robots but yet are often used to teach skills flexibly to other humans and to children in particular. A potential route toward natural and efficient learning and teaching in Human-Robot Interaction (HRI) is to leverage the social competences of humans and the underlying interactional mechanisms. In this perspective, this article discusses the importance of pragmatic frames as flexible interaction protocols that provide important contextual cues to enable learners to infer new action or language skills and teachers to convey these cues. After defining and discussing the concept of pragmatic frames, grounded in decades of research in developmental psychology, we study a selection of HRI work in the literature which has focused on learning-teaching interaction and analyze the interactional and learning mechanisms that were used in the light of pragmatic frames. This allows us to show that many of the works have already used in practice, but not always explicitly, basic elements of the pragmatic frames machinery. However, we also show that pragmatic frames have so far been used in a very restricted way as compared to how they are used in human-human interaction and argue that this has been an obstacle preventing robust natural multi-task learning and teaching in HRI. In particular, we explain that two central features of human pragmatic frames, mostly absent of existing HRI studies, are that (1) social peers use rich repertoires of frames, potentially combined together, to convey and infer multiple kinds of cues; (2) new frames can be learnt continually, building on existing ones, and guiding the interaction toward higher levels of complexity and expressivity. To conclude, we give an outlook on the future research direction describing the relevant key challenges that need to be solved for leveraging pragmatic frames for robot learning and teaching.
Year
DOI
Venue
2016
10.3389/fnbot.2016.00010
FRONTIERS IN NEUROROBOTICS
Keywords
Field
DocType
robot learning,robot teaching,human-robot interaction,pragmatic frames,social learning,language learning,action learning,cognitive developmental robotics
Robot learning,Cognitive robotics,Competence (human resources),Communication,Computer science,Action learning,Developmental robotics,Language acquisition,Social learning,Artificial intelligence,Machine learning,Human–robot interaction
Journal
Volume
ISSN
Citations 
10
1662-5218
3
PageRank 
References 
Authors
0.67
40
4
Name
Order
Citations
PageRank
Anna-Lisa Vollmer1133.47
Britta Wrede256260.31
Katharina J. Rohlfing317217.37
Pierre-yves Oudeyer41209104.05