A General Framework for Reasoning On Inconsistency
By: by Maria Vanina Martinez, Cristian Molinaro, V.S. Subrahmanian, Leila Amgoud
Contributors: Molinaro, Cristian; Subrahmanian, V. S.; Amgoud, Leila; SpringerLink (Online service)
Series: SpringerBriefs in Computer Science
Publisher: Springer New York; Imprint: Springer
Published: 2013
Place of publication: New York, NY
Language: eng
Format: [electronic resource] /
Number of pages: 45
ISBN-13: 9781461467502
Subjects: Mathematical Logic and Formal Languages; Data Mining and Knowledge Discovery; Database management; Logic design; Logics and Meanings of Programs; Artificial Intelligence (incl. Robotics); Data mining; Artificial intelligence; Computer science
Description: This SpringerBrief proposes a general framework for reasoning about inconsistency in a wide variety of logics, including inconsistency resolution methods that have not yet been studied.  The proposed framework allows users to specify preferences on how to resolve inconsistency when there are multiple ways to do so. This empowers users to resolve inconsistency in data leveraging both their detailed knowledge of the data as well as their application needs. The brief shows that the framework is well-suited to handle inconsistency in several logics, and provides algorithms to compute preferred options. Finally, the brief shows that the framework not only captures several existing works, but also supports reasoning about inconsistency in several logics for which no such methods exist today.
Table of contents: title: Introduction and Preliminary Concepts; title: A General Framework for Handling Inconsistency; title: Algorithms; title: Handling Inconsistency in Monotonic Logics; title: Link with Existing Approaches; title: Conclusions.