Effcient minimal model generation using branching lemmas

Ryuzo Hasegawa, Hiroshi Fujita, Miyuki Koshimura

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

13 被引用数 (Scopus)

抄録

An effcient method for minimal model generation is presented. The method employs branching assumptions and lemmas so as to prune branches that lead to nonminimal models, and to reduce minimality tests on obtained models. This method is applicable to other approaches such as Bry's complement splitting and constrained search or Niemelä's groundedness test, and greatly improves their effciency.We implemented MM-MGTP based on the method. Experimental results with MM-MGTP show a remarkable speedup compared to MM-SATCHMO.

本文言語英語
ホスト出版物のタイトルAutomated Deduction - CADE-17 - 17th International Conference on Automated Deduction, Proceedings
編集者David McAllester
出版社Springer Verlag
ページ184-199
ページ数16
ISBN(電子版)3540676643, 9783540676645
DOI
出版ステータス出版済み - 2000
イベント17th International Conference on Automated Deduction, CADE 2000 - Pittsburgh, 米国
継続期間: 6 17 20006 20 2000

出版物シリーズ

名前Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
1831
ISSN(印刷版)0302-9743

その他

その他17th International Conference on Automated Deduction, CADE 2000
国/地域米国
CityPittsburgh
Period6/17/006/20/00

All Science Journal Classification (ASJC) codes

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

フィンガープリント

「Effcient minimal model generation using branching lemmas」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル