Human-robot Co-learning for fluent collaborations

Emma M. Van Zoelen, Karel Van Den Bosch, Mark Neerincx

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationHRI 2021 - Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction
Number of pages3
ISBN (Electronic)9781450382908
Publication statusPublished - 2021
Event2021 ACM/IEEE International Conference on Human-Robot Interaction, HRI 2021 - Virtual, Online, United States
Duration: 8 Mar 202111 Mar 2021

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
ISSN (Electronic)2167-2148


Conference2021 ACM/IEEE International Conference on Human-Robot Interaction, HRI 2021
Country/TerritoryUnited States
CityVirtual, Online


  • Co-adaptation
  • Co-learning
  • Human-agent teaming
  • Human-robot collaboration
  • Interaction patterns


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