Modeling and Evaluation of Expert Systems in Decisionmaking Organizations.
MASSACHUSETTS INST OF TECH CAMBRIDGE LAB FOR INFORMATION AND DECISION SYSTEMS
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The introduction of expert systems as decision aids in decisionmaking organizations will modify their performance. First, a model of symbolic computation with fuzzy logic, using Predicate Transition Nets, is presented. The basic operators AND, OR, and NOT are then used to model the most common kind of expert systems the consultant expert system in which production rules are used for knowledge representation. This model allows to simulate the dynamical behavior of the expert system in its search for a solution and to evaluate its response time for a given input. This response time depends on the number of rules scanned by the system and on the number of interactions with the user. An Air Defense Command and Control application, involving a hierarchical organization, where the expert system is used as an aid in the fusion of inconsistent information, is then developed. A strategy involving the use of the expert system is compared to two other strategies expected to be used by a decision making facing this problem. Measures of performance workload, timeliness, and accuracy are evaluated for each of these strategies. The results show that the use of the expert system improves significantly the accuracy of the organization, but requires more time and increases the workload of the decision making using it.
- Administration and Management
- Human Factors Engineering and Man Machine Systems