Abstract
D-FLAT is a framework for developing algorithms that solve computational problems by dynamic programming on a tree decomposition of the problem instance. The dynamic programming algorithm is specified by means of Answer-Set Programming (ASP), allowing for declarative and succinct specifications. D-FLAT traverses the tree decomposition and calls an ASP system with the provided specification at each tree decomposition node. It is thus crucial that the evaluation of the ASP program is done in an efficient way. As experiments have shown, problems that include weights or more involved arithmetics slow down this step significantly due to the grounding step in ASP, which yields large ground programs in these cases. To overcome this problem, we equip D-FLAT with built-in counters in order to shift certain computations from the ASP side to the internal part of D-FLAT. In this paper, we highlight this new feature and provide empirical benchmarks on weighted versions of the Dominating Set problem showing that our new version increases D-FLAT’s robustness and efficiency.
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- 1.
In [4] it was shown that the treewidth of metro and urban train systems even of large cities like Singapore is relatively small and often not much higher than 5 or 6.
- 2.
Free software, available at github.com/mabseher/htd.
- 3.
Each node n has at most two child nodes; in case of two child nodes, the bags of n and its children contain the same vertices.
- 4.
- 5.
See www.dbai.tuwien.ac.at/proj/dflat/system/files/counters.zip for such an encoding example.
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Acknowledgments
This work has been supported by the Austrian Science Fund (FWF): P25607-N23, Y698-N23. The authors thank the reviewers for their helpful comments which allowed to clarify the presentation of our work in the final version of this paper.
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Abseher, M., Moldovan, M., Woltran, S. (2016). Providing Built-In Counters in a Declarative Dynamic Programming Environment. In: Friedrich, G., Helmert, M., Wotawa, F. (eds) KI 2016: Advances in Artificial Intelligence. KI 2016. Lecture Notes in Computer Science(), vol 9904. Springer, Cham. https://doi.org/10.1007/978-3-319-46073-4_1
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