Planning with Trust for Human-Robot Collaboration

Trust is essential for human-robot collaboration and user adoption of autonomous systems, such as robot assistants. This paper introduces a computational model which integrates trust into robot decision-making. Specifically, we learn from data a partially observable Markov decision process (POMDP) w...

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Veröffentlicht in:	2018 13th ACM/IEEE International Conference on Human-Robot Interaction (HRI) S. 307 - 315
Hauptverfasser:	Chen, Min, Nikolaidis, Stefanos, Soh, Harold, Hsu, David, Srinivasa, Siddhartha
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	New York, NY, USA ACM 26.02.2018
Schriftenreihe:	ACM Conferences
Schlagworte:	Collaboration Computational modeling Computing methodologies > Artificial intelligence > Planning and scheduling > Planning under uncertainty Data models Decision making Fluids Human-centered computing > Human computer interaction (HCI) > Interaction paradigms > Collaborative interaction Human-robot collaboration Human-robot interaction Markov decision process (POMDP) Markov processes Partially observable Trust models human-robot collaboration trust models partially observable markov decision process (pomdp)
ISBN:	9781450349536, 1450349536
ISSN:	2167-2148
Online-Zugang:	Volltext
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