Two transformations of clauses into constraints and their properties for cost-based hypothetical reasoning

Yutaka Matsuo, Mitsuru Ishizuka

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

7 Citations (Scopus)

Abstract

This paper describes two ways to transform propositional clauses into mathematical constraints, and gives an overview of mathematical optimization approaches to inference. The first transformation, which translates constraints into linear inequalities, has been applied to cost-based abduction in the past and showed good performance. The second one, which produces nonlinear equalities, is commonly used in other representations, such as SAT. We clarify their differences and advantages, and show the radical performance transition of linear inequalities. We are mainly targeting at cost-based hypothetical reasoning (or abduction), but through preprocessing, the discussion has generality.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages118-127
Number of pages10
Volume2417
ISBN (Print)3540440380, 9783540440383
Publication statusPublished - 2002
Externally publishedYes
Event7th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2002 - Tokyo, Japan
Duration: 2002 Aug 182002 Aug 22

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2417
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other7th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2002
Country/TerritoryJapan
CityTokyo
Period02/8/1802/8/22

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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