Learning from demonstration (LfD) is a widely-used technique for programming robot
behavior. Despite its flexibility and applicability to a wide range of tasks, LfD is most typically …

We are interested in developing Learning from Demonstration (LfD) systems that are tailored
to be used by everyday people. We highlight and tackle the issues of skill learning, task …

Learning from Demonstration (LfD) explores techniques for learning a task policy from
examples provided by a human teacher. The field of LfD has grown into an extensive body …

This paper considers the question of whether robots can be effectively programmed for
autonomous social interaction through learning from demonstrations recorded via Wizardof …

How do people teach robots tasks? Here, we focus on main methods and models enabling
humans to teach embodied social agents such as social robots, using natural interaction …

Abstract Robot Learning from Demonstration (RLfD) seeks to enable lay users to encode
desired robot behaviors as autonomous controllers. Current work uses a human's …

Learning from demonstration algorithms enable a robot to learn a new policy based on
demonstrations provided by a teacher. In this article, we explore a novel research direction …

Social interaction will be key to enabling robots and machines in general to learn new tasks
from ordinary people (not experts in robotics or machine learning). Everyday people who …

During human-robot interaction, we want the robot to understand us, and we want to
intuitively understand the robot. In order to communicate with and understand the robot, we …

Robot learning from demonstration (LfD) is a research paradigm that can play an important
role in addressing the issue of scaling up robot learning. Since this type of approach …