Reasoning about Knowledge in Human-Automation Systems (Preliminary Report)

In a supervisory control system the human agent’s 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, therefore, 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 familiar problem from the aviation 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’s agents. To conclude, we discuss planned directions that will extend this new approach, and note several systems in the aviation and human-robot team domains that are part of our research program.

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