2ndWorkshop on Human-Interactive Robot Learning (HIRL)

Reuth Mirsky, Kim Baraka, Taylor Kessler Faulkner, Justin Hart, Harel Yedidsion, Xuesu Xiao, Ifrah Idrees, Ethan K. Gordon

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


With robots poised to enter our daily environments, they will not only need to work for people, but also learn from them. An active area of investigation in the robotics, machine learning, and humanrobot interaction communities is the design of teachable robots that can learn interactively from human input. To refer to these research efforts, we use the umbrella term Human-Interactive Robot Learning (HIRL). While algorithmic solutions for robots learning from people have been investigated in a variety of ways, HIRL, as a fairly new research area, is still lacking: 1) a formal set of definitions to classify related but distinct research problems or solutions, 2) benchmark tasks, interactions, and metrics to evaluate the performance of HIRL algorithms and interactions, and 3) clear long-term research challenges to be addressed by different communities. Last year we began consolidating the needed definitions and vocabulary to enable fruitful discussions between researchers from these interdisciplinary fields, and identified a preliminary list of long, medium, and short-term research problems for the community to tackle, and existing tools and frameworks that can be leveraged to this end. This workshop will build upon these discussions, focusing on promoting the specification and design of HIRL benchmarks.

Original languageEnglish
Title of host publicationHRI 2023 - Companion of the ACM/IEEE International Conference on Human-Robot Interaction
PublisherIEEE Computer Society
Number of pages3
ISBN (Electronic)9781450399708
StatePublished - 13 Mar 2023
Event18th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2023 - Stockholm, Sweden
Duration: 13 Mar 202316 Mar 2023

Publication series

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


Conference18th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2023

Bibliographical note

Publisher Copyright:
© 2023 IEEE Computer Society. All rights reserved.


  • Interactive robot learning
  • Learning from human input
  • Socially intelligent robots
  • Socially interactive learning


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