Human-Interactive Robot Learning (HIRL)

With robots poised to enter our daily environments, we conjecture that 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 robotic agents that can l...

Full description

Saved in:
Bibliographic Details
Published in:2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI) pp. 1278 - 1280
Main Authors: Mirsky, Reuth, Baraka, Kim, Faulkner, Taylor Kessler, Hart, Justin, Yedidsion, Harel, Xiao, Xuesu
Format: Conference Proceeding
Language:English
Published: IEEE 07.03.2022
Subjects:
Benchmark testing
Conferences
Ethics
Interactive robot learning
Learning from human input
Machine learning algorithms
Measurement
Neuroscience
Pressing
Socially intelligent robots
Socially interactive learning
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:With robots poised to enter our daily environments, we conjecture that 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 robotic agents 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. The main goal of this workshop will be to consolidate relevant recent work falling under the HIRL umbrella into a coherent set of long, medium, and short-term research problems, and identify the most pressing future research goals in this area. As HIRL is a developing research area, this workshop is an opportunity to break the existing boundaries between relevant research communities by developing and sharing a diverse set of benchmark tasks and metrics for HIRL, inspired by other fields including neuroscience, biology, and ethics research.
DOI:10.1109/HRI53351.2022.9889551