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A formal model of diagnostic inference. I. Problem formulation and decomposition. (English) Zbl 0583.68046

This paper introduces a new model of diagnostic problem solving based on a generalization of the set-covering problem. The model formalizes the concepts of (1) whether or not a set of one or more disorders is sufficient to explain a set of occurring manifestations, (2) what a solution is for a diagnostic problem, and (3) how to generate all of the alternative explanations in a problem’s solution. In addition, conditions for decomposing a diagnostic problem into independent subproblems are stated and proven. This model is of interest because it captures several intuitively plausible features of human diagnostic inference, it directly addresses the issue of multiple simultaneous causative disorders, it can serve as a theoretical basis for expert systems for diagnostic problem solving, and it provides a conceptual framework within which to view some recent AI work on diagnostic problem solving in general.

MSC:

68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
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