March 11, 2022
Human-Interactive Robot Learning (HIRL)
at HRI'22
Workshop recordings here.
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, including demonstrations, feedback, advice, corrections, instructions, etc. To refer to these research efforts, we use the umbrella term Human-Interactive Robot Learning (HIRL).
While algorithmic solutions for robots learning from people has 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 is to consolidate relevant recent works falling under the umbrella of HIRL into a coherent set of long, medium, and short-term research problems, and identify the most pressing future research goals. This workshop will also be used to develop and share diverse benchmark tasks and metrics for HIRL. These tasks would ideally span different HRI settings that are not necessarily restricted by the robotic platform.
While there has been an increased interest in the topics proposed for this workshop, and many relevant papers have been published in the last five years, research efforts falling under the HIRL umbrella are disparate across different communities. Thus, we conjecture that this is the right time to set up a workshop that will bring together researchers from these different communities with complementing research agendas to consolidate the lessons that were learned so far, and offer benchmarks to evaluate contributions on. These benchmarks, in turn, will enable researchers to have more productive collaborations and opportunities to better compare their methods and results.
As this workshop aims to draw researchers with some relevant experience, it will first consist of presentations of new or recently published works. Then, the presenters will be divided into working groups, whose participants and discussion topics will be curated according to their interests. Other people who wish to contribute to the discussions are welcome to join one of the study groups that will be formed.
Invited Speakers
The topics of interest for this workshop include, but are not limited to:
Learning from demonstration, learning by imitation, or learning from observation
Inverse reinforcement learning
Interactive reinforcement learning
Robot learning from human feedback (including advice, corrections, etc.)
Standardized task development for HIRL
Evaluation metrics for learners and teachers
Social signal processing for human teaching behaviors
Natural teaching interfaces
Teacher-learner adaptation
Human-guided exploration
Human-in-the-loop lifelong learning