A cost-reducing question-selection algorithm for propositional knowledge-based systems

Authors:
Jinchang Wang
Affiliations:
Division of Professional Studies, The Richard Stockton College of New Jersey, USA 08240
Venue:
Annals of Mathematics and Artificial Intelligence
Year:
2005

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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.