Probabilistic Networks

  • Uffe B. Kjærulff
  • Anders L. Madsen
Part of the Information Science and Statistics book series (ISS, volume 22)


Probabilistic networks are graphical models of (causal) interactions among a set of variables, where the variables are represented as vertices (nodes) of a graph and the interactions (direct dependences) as directed edges (links or arcs) between the vertices. Any pair of unconnected vertices of such a graph indicates (conditional) independence between the variables represented by these vertices under particular circumstances that can easily be read from the graph. Hence, probabilistic networks capture a set of (conditional) dependence and independence properties associated with the variables represented in the network.


Utility Function Bayesian Network Joint Probability Distribution Dynamic Bayesian Network Discrete Random Variable 
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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Uffe B. Kjærulff
    • 1
  • Anders L. Madsen
    • 1
    • 2
  1. 1.Department of Computer ScienceAalborg UniversityAalborgDenmark
  2. 2.HUGIN EXPERT A/SAalborgDenmark

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