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A Monte Carlo Algorithm for Combining Dempster-Shafer Belief Based on Approximate Pre-Computation

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Symbolic and Quantitative Approaches to Reasoning and Uncertainty (ECSQARU 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1638))

Abstract

In his paper, a new Monte Carlo algorithm for combining Dempster-Shafer belief functions is introduced. It is based on the idea of approximate pre-computation, which allows to obtain more accurate estimations by means of carrying out a compilation phase previously to the simulation. Some versions of the new algorithm are experimentally compared to the previous methods.

This work has been supported by CICYT under projects TIC97-1135-C04-01 and TIC97-1135-C04-02.

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References

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Author information

Authors and Affiliations

  1. Dpt. Statistics and Applied Mathematics, University of Almería, 04120, Almería, Spain

    Serafín Moral

  2. Dpt. Computer Science and Artificial Intelligence, University of Granada, 18071, Granada, Spain

    Antonio Salmerón

Authors
  1. Serafín Moral
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  2. Antonio Salmerón
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University College London, Gower Street, WC1E 6BT, London, UK

    Anthony Hunter

  2. Department of Electronic Engineering, University of London, Queen Mary and Westfield College, E1 4NS, London, UK

    Simon Parsons

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© 1999 Springer-Verlag Berlin Heidelberg

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Moral, S., Salmerón, A. (1999). A Monte Carlo Algorithm for Combining Dempster-Shafer Belief Based on Approximate Pre-Computation. In: Hunter, A., Parsons, S. (eds) Symbolic and Quantitative Approaches to Reasoning and Uncertainty. ECSQARU 1999. Lecture Notes in Computer Science(), vol 1638. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48747-6_28

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  • DOI: https://doi.org/10.1007/3-540-48747-6_28

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66131-3

  • Online ISBN: 978-3-540-48747-0

  • eBook Packages: Springer Book Archive

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