Abstract
In many applications of knowledge-based systems, initially given data are often not sufficient to reach a conclusion and more data are needed. A question-selection algorithm is to identify missing information and select proper questions to ask. We present a question-selection algorithm for propositional knowledge-based systems, which aims at asking more relevant and less expensive questions. Comparing to those algorithms currently used in many expert systems, the new algorithm is capable of reaching a conclusion more economically in our computational experiments.
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03B05, 68T20, 68T15
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Wang, J. A cost-reducing question-selection algorithm for propositional knowledge-based systems. Ann Math Artif Intell 44, 35–60 (2005). https://doi.org/10.1007/s10472-005-1809-2
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DOI: https://doi.org/10.1007/s10472-005-1809-2