Similarity-based inconsistency-tolerant logics

Ofer Arieli, Anna Zamansky

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Many logics for AI applications that are defined by denotational semantics are trivialized in the presence of inconsistency. It is therefore often desirable, and practically useful, to refine such logics in a way that inconsistency does not cause the derivation of any formula, and, at the same time, inferences with respect to consistent premises are not affected. In this paper, we introduce a general method of doing so by incorporating preference relations defined in terms of similarities. We exemplify our method for three of the most common denotational semantics (standard many-valued matrices, their non-deterministic generalization, and possible worlds semantics), and demonstrate their usefulness for reasoning with inconsistency.

Original languageEnglish
Title of host publicationLogics in Artificial Intelligence - 12th European Conference, JELIA 2010, Proceedings
Number of pages13
StatePublished - 2010
Externally publishedYes
Event12th European Conference on Logics in Artificial Intelligence, JELIA 2010 - Helsinki, Finland
Duration: 13 Sep 201015 Sep 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6341 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference12th European Conference on Logics in Artificial Intelligence, JELIA 2010

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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