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

Por: Colaborador(es): Tipo de material: TextoTextoSeries SpringerBriefs in Computer ScienceEditor: New York, NY : Springer New York : Imprint: Springer, 2013Descripción: vii, 45 páginas recurso en líneaTipo de contenido:
  • texto
Tipo de medio:
  • computadora
Tipo de portador:
  • recurso en línea
ISBN:
  • 9781461467502
Formatos físicos adicionales: Edición impresa:: Sin títuloClasificación LoC:
  • Q334-342
Recursos en línea:
Contenidos:
Introduction and Preliminary Concepts -- A General Framework for Handling Inconsistency -- Algorithms -- Handling Inconsistency in Monotonic Logics -- Link with Existing Approaches -- Conclusions.
Resumen: 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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Springer eBooks

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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