Print Email Facebook Twitter Human-Robot Co-Learning for Fluent Collaborations Title Human-Robot Co-Learning for Fluent Collaborations Author van Zoelen, E.M. van den Bosch, K. Neerincx, M.A. Publication year 2021 Abstract A team develops competency by progressive mutual adaptation and learning, a process we call co-learning. In human teams, partners naturally adapt to each other and learn while collaborating. This is not self-evident in human-robot teams. There is a need for methods and models for describing and enabling co-learning in human-robot partnerships. The presented project aims to study human-robot co-learning as a process that stimulates fluent collaborations. First, it is studied how interactions develop in a context where a human and a robot both have to implicitly adapt to each other and have to learn a task to improve the collaboration and performance. The observed interaction patterns and learning outcomes will be used to (1) investigate how to design learning interactions that support human-robot teams to sustain implicitly learned behavior over time and context, and (2) to develop a mental model of the learning human partner, to investigate whether this supports the robot in its own learning as well as in adapting effectively to the human partner. Subject Human-robot collaborationCo-learningInteraction patternsCoadaptationHuman-agent teamingHealthy for LifeHealthy Living To reference this document use: http://resolver.tudelft.nl/uuid:c55a8771-238f-45e5-8dfa-b06b1231753c DOI https://doi.org/10.1145/3434074.3446354 TNO identifier 952969 ISBN 9781450382908/21/03 Source HRI '21 Companion: Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction March 2021, 574-576 Document type conference paper Files To receive the publication files, please send an e-mail request to TNO Library.