A cost-reducing question-selection algorithm for propositional knowledge-based systems |
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Authors: | Jinchang Wang |
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Affiliation: | (1) Division of Professional Studies, The Richard Stockton College of New Jersey, NJ 08240, USA |
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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.
AMS subject classification 03B05, 68T20, 68T15 |
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Keywords: | knowledge-based system inference engine proposition |
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