2nd Workshop on Human-Interactive Robot Learning
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 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.
3) clear long-term research challenges to be addressed by different communities.
The topics of interest for this workshop include, but are not limited to: