Heuristic Algorithms for the Triangulation of Graphs

  title={Heuristic Algorithms for the Triangulation of Graphs},
  author={Andr{\'e}s Cano and Seraf{\'i}n Moral},
Dierent uncertainty propagation algorithms in graph-ical structures can be viewed as a particular case of propagation in a joint tree, which can be obtained from dierent triangulations of the original graph. The complexity of the resulting propagation algorithms depends on the size of the resulting triangulated graph. The problem of obtaining an optimum graph triangulation is known to be NP-complete. Thus approximate algorithms which nd a good triangulation in reasonable time are of particular… CONTINUE READING
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Publications referenced by this paper.
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Evaluating in uence diagrams

D. ShachterR.
Operations Research • 1986

Probability Propagation

P. ShenoyP.
Annals of Mathematical and Arti cial Intelligence

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