Similarity-based inconsistency-tolerant logics

Ofer Arieli; Anna Zamansky

doi:10.1007/978-3-642-15675-5_4

Similarity-based inconsistency-tolerant logics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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 language	English
Title of host publication	Logics in Artificial Intelligence - 12th European Conference, JELIA 2010, Proceedings
Pages	11-23
Number of pages	13
DOIs	https://doi.org/10.1007/978-3-642-15675-5_4
State	Published - 2010
Externally published	Yes
Event	12th European Conference on Logics in Artificial Intelligence, JELIA 2010 - Helsinki, Finland Duration: 13 Sep 2010 → 15 Sep 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6341 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	12th European Conference on Logics in Artificial Intelligence, JELIA 2010
Country/Territory	Finland
City	Helsinki
Period	13/09/10 → 15/09/10

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-15675-5_4

Cite this

Arieli, O., & Zamansky, A. (2010). Similarity-based inconsistency-tolerant logics. In Logics in Artificial Intelligence - 12th European Conference, JELIA 2010, Proceedings (pp. 11-23). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6341 LNAI). https://doi.org/10.1007/978-3-642-15675-5_4

@inproceedings{6a18f05272904151b2d915048c97b79a,

title = "Similarity-based inconsistency-tolerant logics",

abstract = "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.",

author = "Ofer Arieli and Anna Zamansky",

year = "2010",

doi = "10.1007/978-3-642-15675-5_4",

language = "English",

isbn = "3642156746",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "11--23",

booktitle = "Logics in Artificial Intelligence - 12th European Conference, JELIA 2010, Proceedings",

note = "12th European Conference on Logics in Artificial Intelligence, JELIA 2010 ; Conference date: 13-09-2010 Through 15-09-2010",

}

Arieli, O & Zamansky, A 2010, Similarity-based inconsistency-tolerant logics. in Logics in Artificial Intelligence - 12th European Conference, JELIA 2010, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6341 LNAI, pp. 11-23, 12th European Conference on Logics in Artificial Intelligence, JELIA 2010, Helsinki, Finland, 13/09/10. https://doi.org/10.1007/978-3-642-15675-5_4

Similarity-based inconsistency-tolerant logics. / Arieli, Ofer; Zamansky, Anna.
Logics in Artificial Intelligence - 12th European Conference, JELIA 2010, Proceedings. 2010. p. 11-23 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6341 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Similarity-based inconsistency-tolerant logics

AU - Arieli, Ofer

AU - Zamansky, Anna

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=78049412370&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-15675-5_4

DO - 10.1007/978-3-642-15675-5_4

M3 - Conference contribution

AN - SCOPUS:78049412370

SN - 3642156746

SN - 9783642156748

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 11

EP - 23

BT - Logics in Artificial Intelligence - 12th European Conference, JELIA 2010, Proceedings

T2 - 12th European Conference on Logics in Artificial Intelligence, JELIA 2010

Y2 - 13 September 2010 through 15 September 2010

ER -

Similarity-based inconsistency-tolerant logics

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this