On the Practical Significance of Hypertree vs. TreeWidth

Authors:
Rina Dechter;Lars Otten;Radu Marinescu
Affiliations:
Bren School of Information and Computer Sciences, University of California, Irvine, CA 92697-3435. Email: dechter@ics.uci.edu;Bren School of Information and Computer Sciences, University of California, Irvine, CA 92697-3435. Email: lotten@ics.uci.edu;Cork Constraint Computation Centre, Department of Computer Science, University College Cork, Ireland. Email: r.marinescu@4c.ucc.ie
Venue:
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Year:
2008

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Abstract

The recently introduced notion of hypertree width has been shown to provide a broader characterization of tractable constraint and probabilistic networks than the tree width. This paper demonstrates empirically that in practice the bounding power of the tree width is still superior to the hypertree width for many benchmark instances of both probabilistic and deterministic networks.