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Recent advances in the artificial intelligence technology of knowledge-based expert systems have captivated the imaginations of designers, sponsors, and suppliers of computer-based systems in government and industry as well as researchers in university and non-profit laboratories where the technology originated. An expert system is essentially a way to capture the knowledge and expertise of a subject-matter expert and transfer it to a computer program in hopes of creating an “intelligent” computer system that will emulate the problem-solving and decision-making performance of the expert. Such systems are being built to serve as intelligent advisors and decision aids in a wide variety of application areas. We discuss conceptual issues underlying expert system design, with references to current psychological and artificial intelligence literature, and urge Consideration of these issues before undertaking development of expert systems.

The Speech Intelligibility Index (SII) was measured for Navy divers participating in two saturation deep dives and for a group of nondivers to test different communication systems and their components. These SIIs were validated using the Speech Perception in Noise (SPIN) test and the Griffiths version of the Modified Rhyme Test (GMRT). Our goal was to determine if either of these assessments was sensitive enough to provide an objective measure of speech intelligibility when speech was processed through different helmets and helium speech unscramblers (HSUs). Results indicated that SII values and percent intelligibility decreased incrementally as background noise level increased. SIIs were very reliable across the different groups of subjects indicating that the SII was a strong measurement for predicting speech intelligibility to compare linear system components such as helmets. The SII was not useful in measuring intelligibility through nonlinear devices such as HSUs. The speech intelligibility scores on the GMRT and SPIN tests were useful when the system component being compared had a large measurable difference, such as in helmet type. However, when the differences were more subtle, such as differences in HSUs, neither the SPIN nor the GMRT appeared sensitive enough to make such distinctions. These results have theoretical as well as practical value for measuring the quality and intelligibility of helium speech enhancement systems.

We abserved subjects performing a task In a dynamic environment using rule-based supervisory control (RBSC). Task performance was evaluated in an experiment using control and display features derived from a Cognitive process model of RBSC. In particular, the effects of numerical versus graphical display of rule parameters, textual data entry versus direct manipulation for contrd of rule parameters, and the presence or absence of a display of the history of past actions were examined. Results indicate that the way in which subjects use the automation is affected by the controls and displays provided, and that the nature of that use can affect overall task performance. L lNTRODUCIlONRule-based supervisory control (RBSC) is a mechanism whereby users of complex computer-based systems, such as decision support systems, can interpret extemal events and take actions in the world through the use of rules they have previously specified and entered into their systems in anticipation of such events. The defining characteristic of RBSC is this use of user-specified conditional response rules as one aspect of system operation; user-system communication in RBSC includes explicit rules, independent of any internal system implementation considerations. Our research addresses questions concerning both the cognitive processes involved in the performance of realistic tactical tasks by subjects knowledgeable in RBSC and the design of displays and controls for RBSC systems.In previous work [l], [21, [3], [4], we have developed a cognitive process model of RBSC which is based on empirical observations of subjects responding to events occurring in a realistic simulation of a naval combat direction system environment. In [3] we reported on the observation of subjects with experience in RBSC or naval tactical operations. We have since carried out similar observations of naive subjects; the resulting data are still under review, but initial indications show no significant differences relative to the model between the groups. The current state of this model is shown in Fig. 1. In the model, events occurring in the environment are responded to by automatic actions specified in advance Manuscript received 1 August 1992. This work was supported by the JHUIAF'L Independent Research and Development program.through condition-action rules and by manual actions taken by the decision maker in response to the dynamics of the situation at hand. The decision maker also observes both automatic and manual actions, and these observations are accumulated and compared with expectancies generated both during an earlier planning phase devoted to making preparations for the expected situation and during replanning that may become desirable and feasible during the course of the evolving situation. Discrepancies arising between observations and expectancies are accumulated, and replanning activity is triggered when the accumulation of discrepancies passes some threshold 141.In the empirical observations of subjects performing realistic decision-making tasks in ...