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Computing Probabilities of Events in Bayesian Networks

  • Rolf Haenni
  • Jürg Kohlas
  • Norbert Lehmann
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 90)

Abstract

This paper proposes a new approach for computing probabilities of events in Bayesian networks. The idea is to replace the outward phase of the propagation algorithm by a second (partial) inward propagation phase. The benefit of this idea is that the attention can be focussed on optimizing the inward phase.1

Keywords

Bayesian Network Normalization Constant Belief Function Unique Path Incoming Message 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Rolf Haenni
    • 1
  • Jürg Kohlas
    • 2
  • Norbert Lehmann
    • 2
  1. 1.Computer Science DepartmentUniversity of CaliforniaLos AngelesUSA
  2. 2.Department of InformaticsUniversity of FribourgSwitzerland

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