Ordered binary decision diagrams as knowledge-bases

  • Authors:
  • Takashi Horiyama;Toshihide Ibaraki

  • Affiliations:
  • Nara Institute of Science and Technology, Nara, Japan;Kyoto Univ., Japan

  • Venue:
  • Artificial Intelligence
  • Year:
  • 2002

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Abstract

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.