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)

Electronic version of the publication:

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