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Contributions to Proceedings:

T. Peitl, F. Slivovsky, S. Szeider:
"Dependency Learning for QBF";
in: "Theory and Applications of Satisfiability Testing - SAT 2017", Springer International Publishing AG 2017, 2017, ISBN: 978-3-319-66263-3, 198 - 313.



English abstract:
Decomposition width parameters such as treewidth provide a measurement on the complexity of a graph. Finding a decomposition of smallest width is itself NP-hard but lends itself to a SAT-based solution. Previous work on treewidth, branchwidth and clique-width indicates that identifying a suitable characterization of the considered decomposition method is key for a practically feasible SAT-encoding.

In this paper we study SAT-encodings for the decomposition width parameters special treewidth and pathwidth. In both cases we develop SAT-encodings based on two different characterizations. In particular, we develop two novel characterizations for special treewidth based on partitions and elimination orderings. We empirically obtained SAT-encodings.


"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
http://dx.doi.org/10.1007/978-3-319-66263-3_27

Electronic version of the publication:
https://link.springer.com/chapter/10.1007%2F978-3-319-66263-3_27


Created from the Publication Database of the Vienna University of Technology.