Abstract model generation for preprocessing clause sets

Miyuki Koshimura, Mayumi Umeda, Ryuzo Hasegawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Abstract model generation refers to model generation for abstract clause sets in which arguments of atoms are ignored. We give two abstract clause sets which are obtained from normal clause sets. One is for checking satisfiability of the original normal clause set, Another is used for eliminating unnecessary clauses from the original one. These abstract clause sets are propositional, i.e. decidable. Thus, we can use them for preprocessing the original one.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages67-78
Number of pages12
Volume3452 LNAI
Publication statusPublished - 2005
Event11th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning, LPAR 2004 - Montevideo, Uruguay
Duration: Mar 14 2005Mar 18 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3452 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning, LPAR 2004
CountryUruguay
CityMontevideo
Period3/14/053/18/05

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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Koshimura, M., Umeda, M., & Hasegawa, R. (2005). Abstract model generation for preprocessing clause sets. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3452 LNAI, pp. 67-78). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3452 LNAI).