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Output details

11 - Computer Science and Informatics

University of Huddersfield

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Output 27 of 54 in the submission

Article title

Minimal change: Relevance and recovery revisited

Type

D - Journal article

DOI

10.1016/j.artint.2013.06.001

Title of journal

Artificial Intelligence

Article number

Volume number

201

Issue number

First page of article

ISSN of journal

0004-3702

Year of publication

2013

URL

http://dx.doi.org/10.1016/j.artint.2013.06.001

Number of additional authors

Additional information

<22>This paper is the first to achieve applicability of AGM belief revision principles to modern knowledge representation languages, such as rule systems and description logics, in a principled way. The paper shows that using relevance instead of recovery allows for the the AGM principles to be adapted for a much broader collection of contemporary KR languages. This is a milestone towards the utilization of belief revision principles in the evolution of knowledge on the semantic web, and led to the setting up of the recent EU-funded projects DIACHRON and PRELIDA. AIJ is the most prestigious AI journal.

Interdisciplinary

Cross-referral requested

Research group

None

Citation count

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract