TY - GEN
T1 - 3rd Workshop on Human-Interactive Robot Learning (HIRL)
AU - Racca, Mattia
AU - Mirsky, Reuth
AU - Senft, Emmanuel
AU - Xiao, Xuesu
AU - Idrees, Ifrah
AU - Kshirsagar, Alap
AU - Prakash, Ravi
N1 - Publisher Copyright: © 2024 Copyright held by the owner/author(s)
PY - 2024/3/11
Y1 - 2024/3/11
N2 - 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.
AB - 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.
KW - Interactive robot learning
KW - Learning from human input
KW - Socially intelligent robots
KW - Socially interactive learning
UR - http://www.scopus.com/inward/record.url?scp=85188129797&partnerID=8YFLogxK
U2 - 10.1145/3610978.3638160
DO - 10.1145/3610978.3638160
M3 - Conference contribution
T3 - ACM/IEEE International Conference on Human-Robot Interaction
SP - 1349
EP - 1351
BT - HRI 2024 Companion - Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction
T2 - 19th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2024
Y2 - 11 March 2024 through 15 March 2024
ER -