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Extreme Points of the Credal Sets Generated by Elementary Comparative Probabilities

  • Conference paper
Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7958))

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Abstract

When using convex probability sets (or, equivalently, lower previsions) as models of uncertainty, identifying extreme points can be useful to perform various computations or to use some algorithms. In general, sets induced by specific models such as possibility distributions, linear vacuous mixtures or 2-monotone measures may have extreme points easier to compute than generic convex sets. In this paper, we study extreme points of another specific model: comparative probability orderings between the elements of a finite space. We use these extreme points to study the properties of the lower probability induced by this set, and connect comparative probabilities with other uncertainty models.

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Author information

Authors and Affiliations

  1. Dept. of Statistics and O.R., University of Oviedo, Oviedo, Spain

    Enrique Miranda

  2. CNRS, HEUDIASYC Joint Research Unit, Compiègne, France

    Sébastien Destercke

Authors
  1. Enrique Miranda
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  2. Sébastien Destercke
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Editor information

Editors and Affiliations

  1. Department of Information and Computing Sciences, Utrecht University, Princetonplein 5, 3584 CC, Utrecht, The Netherlands

    Linda C. van der Gaag

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Miranda, E., Destercke, S. (2013). Extreme Points of the Credal Sets Generated by Elementary Comparative Probabilities. In: van der Gaag, L.C. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2013. Lecture Notes in Computer Science(), vol 7958. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39091-3_36

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  • DOI: https://doi.org/10.1007/978-3-642-39091-3_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39090-6

  • Online ISBN: 978-3-642-39091-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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