Probabilistic reference and grounding with PRAGR for dialogues with robots

In this paper, we present a system for effective referential human-robot communication in the face of perceptual deviation using the Probabilistic Reference And GRounding mechanism PRAGR and vague feature models based on prototypes. PRAGR can handle descriptions of arbitrary complexity including spatial relations and uses flexible concept assignment in generation and resolution of referring expressions for bridging conceptual gaps in referential robot-robot or human-robot interaction. We evaluate the benefit of using vague as compared to crisp properties regarding referential success and robustness towards perspective alignment error in referential robot-robot and human-robot communication.

Metadaten
Author details:	Vivien Mast, Zoe Falomir, Diedrich Wolter
DOI:	https://doi.org/10.1080/0952813X.2016.1154611
ISSN:	0952-813X
ISSN:	1362-3079
Title of parent work (English):	Zeitschrift fÃ¼r pÃ¤dagogische Psychologie.
Publisher:	Hogrefe
Place of publishing:	Abingdon
Publication type:	Article
Language:	English
Year of first publication:	2016
Publication year:	2016
Release date:	2020/03/22
Tag:	Reference handling; dialogue; human-machine interaction; perceptual deviation; symbol grounding; vagueness
Volume:	28
Number of pages:	23
First page:	889
Last Page:	911
Funding institution:	Deutsche Forschungsgemeinschaft (DFG) [SFB/TR 8, I5-[DiaSpace]]; European Commission through FP7 Marie Curie IEF actions under project COGNITIVE-AMI [GA 328763]; Universitat Bremen under project Cognitive Qualitative Descriptions and Applications (CogQDA); Technologieallianz Oberfranken (TAO)
Peer review:	Referiert
Institution name at the time of the publication:	Humanwissenschaftliche Fakultät / Exzellenzbereich Kognitionswissenschaften