Model-based communicative acts: human-computer collaboration in supervisory control

Abstract Supervisory control environments can be characterized as dynamic, complex, uncertain, and risky. The cognitive demands placed on human supervisory controllers are driven by the continual need for situation assessment (including active information seeking), active goal-setting and planning, and anticipatory as well as reactive control actions and compensating for abnormal system conditions. One way to improve the human-machine system is with intelligent support systems that provide context-sensitive displays, dialogue, and resources for activity management. The Georgia Tech Mission Operations Cooperative Assistant (GT-MOCA) is an example of such a system for NASA satellite ground control. The design of GT-MOCA is based on (1) principles of human-computer cooperative problem solving, partly derived from an analysis of human communication literature, (2) empirical study of the use of an existing real-time expert system for satellite ground control, and (3) the OFMspert architecture which provides dynamic intent inferencing organized around the operator function model. GT-MOCA provides three major resources for cooperative support: interactive graphics of system components, an inspectable and interactive visualization of current activity requirements, and message lists organized around major communicative functions such as advice and various types of alerts. This paper focuses on the representation of the communicative acts that are the underpinning of these message lists and details how such acts are integrated into the operator function model of activity. An analysis of GT-MOCA with respect to human communication literature and an empirical evaluation of GT-MOCA show that it does support relevant and timely interaction with human problem solvers and does provide some performance benefits.