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Ordered binary decision diagrams as knowledge-bases
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DOI：10.1016/S0004-3702(02)00119-4.png)
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Abstract
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We consider the use of ordered binary decision diagrams (OBDDs) as a means of realizing knowledge-bases, and show that, from the view point of space requirement, the OBDD-based representation is more efficient and suitable in some cases, compared with the traditional CNF-based and/or model-based representations. We then present polynomial time algorithms for the two problems of testing whether a given OBDD represents a unate Boolean function, and of testing whether it represents a Horn function. (C) 2002 Published by Elsevier Science B.V.
Keywords:
knowledge representation
automated reasoning
ordered binary decision diagrams (OBDDs)
recognition problems
unate functions
Horn functions
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