3rd Workshop on Human-Interactive Robot Learning (HIRL)

Mattia Racca, Reuth Mirsky, Emmanuel Senft, Xuesu Xiao, Ifrah Idrees, Alap Kshirsagar, Ravi Prakash

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

Abstract

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 human-robot interaction communities is the design of teachable robots that can learn interactively from humans. To refer to these research efforts, we use the umbrella term Human-Interactive Robot Learning (HIRL). In the last two years, we began consolidating what defines HIRL in terms of long, medium, and short-term research problems and what the different communities can contribute to those problems. With this third installment of the HIRL workshop, we aim at further consolidating this community and, specifically this year, discuss how the recent widespread of Large Language Models (LLMs) will impact the teaching of robots and explore the opportunities and challenges presented by robots' nature of embodied agents.

Original languageEnglish
Title of host publicationHRI 2024 Companion - Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction
PublisherIEEE Computer Society
Pages1349-1351
Number of pages3
ISBN (Electronic)9798400703232
DOIs
StatePublished - 11 Mar 2024
Event19th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2024 - Boulder, United States
Duration: 11 Mar 202415 Mar 2024

Publication series

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

Conference

Conference19th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2024
Country/TerritoryUnited States
CityBoulder
Period11/03/2415/03/24

Bibliographical note

Publisher Copyright:
© 2024 Copyright held by the owner/author(s)

Keywords

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

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