In the context of robotics and automation, learning from demonstration (LfD) is the paradigm
in which robots acquire new skills by learning to imitate an expert. The choice of LfD over …

This article surveys the use of natural language in robotics from a robotics point of view. To
use human language, robots must map words to aspects of the physical world, mediated by …

Regardless of how much data artificial intelligence agents have available, agents will
inevitably encounter previously unseen situations in real-world deployments. Reacting to …

Recent rapid advances in Artificial Intelligence (AI) and Machine Learning have raised many
questions about the regulatory and governance mechanisms for autonomous machines …

Interactive Machine Learning (IML) seeks to complement human perception and intelligence
by tightly integrating these strengths with the computational power and speed of computers …

Intelligent systems that learn interactively from their end-users are quickly becoming
widespread. Until recently, this progress has been fueled mostly by advances in machine …

How can end users efficiently influence the predictions that machine learning systems make
on their behalf? This paper presents Explanatory Debugging, an approach in which the …

The wide adoption of Machine Learning (ML) technologies has created a growing demand
for people who can train ML models. Some advocated the term" machine teacher''to refer to …

The question of whether AI systems such as robots can or should be afforded moral agency
or patiency is not one amenable either to discovery or simple reasoning, because we as …

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 …