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Semantic Splitting of Conditional Belief Bases

  • 2021
  • OriginalPaper
  • Chapter
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Abstract

The chapter delves into the intricacies of semantic splitting of conditional belief bases, a technique that allows for the decomposition of complex belief bases into smaller, more manageable parts. By leveraging ordinal conditional functions (OCFs) and ranking functions, the authors present a method that not only aligns with syntax splitting but also extends it to semantic and constraint splittings. The paper introduces the concept of constraint splitting, showing how it can capture and exceed syntax splittings, offering a more robust and efficient approach to nonmonotonic reasoning. The authors also discuss the application of these methods to c-representations, highlighting their practical implications and potential for further research in the field.

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Title
Semantic Splitting of Conditional Belief Bases
Authors
Christoph Beierle
Jonas Haldimann
Gabriele Kern-Isberner
Copyright Year
2021
DOI
https://doi.org/10.1007/978-3-030-76020-5_5
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