Knowledge base reformation: Preparing first-order theories for efficient propositional reasoning

Helmut Prendinger, Mitsuru Ishizuka, Gerhard Schurz

研究成果: Article査読

1 被引用数 (Scopus)

抄録

We present an approach to knowledge compilation that transforms a function-free first-order Horn knowledge base to propositional logic. This form of compilation is important since the most efficient reasoning methods are defined for propositional logic, while knowledge is most conveniently expressed within a first-order language. To obtain compact propositional representations, we employ techniques from (ir)relevance reasoning as well as theory transformation via unfold/fold transformations. Application areas include diagnosis, planning, and vision. Preliminary experiments with a hypothetical reasoner indicate that our method may yield significant speed-ups.

本文言語English
ページ(範囲)35-57
ページ数23
ジャーナルInternational Journal of Pattern Recognition and Artificial Intelligence
14
1
DOI
出版ステータスPublished - 2000 2月
外部発表はい

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ ビジョンおよびパターン認識
  • 制御およびシステム工学

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