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Part of the book series: Information Science and Statistics ((ISS))

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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.

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© 2008 Springer Science+Business Media, LLC

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(2008). Networks. In: Bayesian Networks and Influence Diagrams. Information Science and Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-74101-7_2

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