  As robotic teammates become more common in society, people will assess the
robots' roles in their interactions along many dimensions. One such dimension
is effectiveness: people will ask whether their robotic partners are
trustworthy and effective collaborators. This begs a crucial question: how can
we quantitatively measure the helpfulness of a robotic partner for a given task
at hand? This paper seeks to answer this question with regards to the
interactive robot's decision making. We describe a clear, concise, and
task-oriented metric applicable to many different planning and execution
paradigms. The proposed helpfulness metric is fundamental to assessing the
benefit that a partner has on a team for a given task. In this paper, we define
helpfulness, illustrate it on concrete examples from a variety of domains,
discuss its properties and ramifications for planning interactions with humans,
and present preliminary results.
