  In a supervisory control system the human agent knowledge of past, current,
and future system behavior is critical for system performance. Being able to
reason about that knowledge in a precise and structured manner is central to
effective system design. In this paper we introduce the application of a
well-established formal approach to reasoning about knowledge to the modeling
and analysis of complex human-automation systems. An intuitive notion of
knowledge in human-automation systems is sketched and then cast as a formal
model. We present a case study in which the approach is used to model and
reason about a classic problem from the human-automation systems literature;
the results of our analysis provide evidence for the validity and value of
reasoning about complex systems in terms of the knowledge of the system agents.
To conclude, we discuss research directions that will extend this approach, and
note several systems in the aviation and human-robot team domains that are of
particular interest.
