d-Separation: From Theorems to Algorithms

An efficient algorithm is developed that identifies all independencies implied by the topology of a Bayesian network. Its correctness and maximality stems from the soundness and completeness of d-separation with respect to probability theory. The algorithm runs in time O ( l E l ) where E is the number of edges in the network.

Authors

• Dan Geiger
• Thomas Verma
• Judea Pearl

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