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

Por: Colaborador(es): Tipo de material: TextoTextoSeries SpringerBriefs in Computer Science | SpringerBriefs in Computer ScienceEditor: New York, NY : Springer New York : Imprint: Springer, 2013Descripción: VII, 45 p. online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • online resource
ISBN:
  • 9781461467502
Trabajos contenidos:
  • SpringerLink (Online service)
Tema(s): Formatos físicos adicionales: Sin títuloClasificación CDD:
  • 006.3 23
Clasificación LoC:
  • Q334-342
  • TJ210.2-211.495
Recursos en línea:
Contenidos:
Springer eBooksResumen: 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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