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A General Framework for Reasoning On Inconsistency [electronic resource] / by Maria Vanina Martinez, Cristian Molinaro, V.S. Subrahmanian, Leila Amgoud.

By: Contributor(s): Material type: TextTextSeries: SpringerBriefs in Computer SciencePublisher: New York, NY : Springer New York : Imprint: Springer, 2013Description: VII, 45 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781461467502
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q334-342
  • TJ210.2-211.495
Online resources:
Contents:
Introduction and Preliminary Concepts -- A General Framework for Handling Inconsistency -- Algorithms -- Handling Inconsistency in Monotonic Logics -- Link with Existing Approaches -- Conclusions.
In: Springer eBooksSummary: 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.
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Introduction and Preliminary Concepts -- A General Framework for Handling Inconsistency -- Algorithms -- Handling Inconsistency in Monotonic Logics -- Link with Existing Approaches -- Conclusions.

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.

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