work formalism; qualitative relationships (i.e., whether one variable directly affects another at all) are reflected in the topology (the links), whereas quantitative details of those dependencies are represented by conditional probability tables.
Gonsalves et al. (1997) describe how this model is used to process low-level data on enemy size, activity, location, and equipment coming in during the course of a red attack and how the situation is continually reassessed during the engagement. A related effort by Illgen et al. (1997b) shows how the approach can be extended to model assessment of enemy courses of action and identification of the most likely course of action selected as the engagement unfolds. Research is now under way, as part of the Federated Laboratory effort supported by the Army Research Laboratory, to develop more extensive belief network models of the situation assessment process for a selected brigade-level engagement. Considerable effort is expected to be devoted to validation of developed models through comparison of model predictions with empirical data.
A number of modeling efforts have also been conducted by Zacharias and colleagues to develop belief network-based situation awareness models of Air Force decision makers. Zacharias et al. (1996) first applied belief networks to model pilot situation awareness in counter-air operations, using them to infer basic mission phases, defensive/offensive strength ratios, and appropriate intercept strategies. Zacharias et al. (1996) built upon this work by including additional factors to incorporate more threat attributes, engagement geometry, and sensor considerations. Work is now under way to refine and validate these situation awareness models and incorporate them into self-contained pilot agents (accounting for other aspects of pilot decision making and flight execution) as part of a larger-scale (M versus N) tactical air combat simulator called man-in-the-loop air to air system performance evaluation model (MIL-AASPEM) (Lawson and Butler, 1995). Parallel efforts are also being conducted to use these situation awareness models for driving tactical displays as a function of the inferred tactical situation (Mulgund et al., 1997) and for providing the battlefield commander with tactical decision aids (Mengshoel and Wilkins, 1997; Schlabach, 1997).
Although there is significant activity regarding the use of belief network-based situation awareness models, it should be emphasized that most of this work has been focused on (1) the knowledge elicitation needed to define the subject matter expert's mental model, (2) the computational model implementation, and (3) the generation of simulation-based traces of the inferencing process and the resulting situation-driven activities of the operator model. Little actual validation has been conducted, and experimental efforts to validate the model output with what is actually observed under well-controlled man-in-the-loop simulator experiments are just now beginning.
We believe that a belief network-based approach to modeling situation assessment has considerable potential, but is not without its drawbacks. First, the graphic representation structure makes explicit, to domain experts and developers