The D-FLAT System for Dynamic Programming on Tree Decompositions

  • Michael Abseher
  • Bernhard Bliem
  • Günther Charwat
  • Frederico Dusberger
  • Markus Hecher
  • Stefan Woltran
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8761)

Abstract

Complex reasoning problems over large amounts of data pose a great challenge for computer science. To overcome the obstacle of high computational complexity, exploiting structure by means of tree decompositions has proved to be effective in many cases. However, the implementation of suitable efficient algorithms is often tedious. D-FLAT is a software system that combines the logic programming language Answer Set Programming with problem solving on tree decompositions and can serve as a rapid prototyping tool for such algorithms. Since we initially proposed D-FLAT, we have made major changes to the system, improving its range of applicability and its usability. In this paper, we present the system resulting from these efforts.

Keywords

Answer Set Programming tree decompositions treewidth 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Abseher, M., Bliem, B., Charwat, G., Dusberger, F., Hecher, M., Woltran, S.: D-FLAT: Progress report. Technical Report DBAI-TR-2014-86, Vienna University of Technology (2014)Google Scholar
  2. 2.
    Arnborg, S., Corneil, D.G., Proskurowski, A.: Complexity of finding embeddings in a k-tree. SIAM J. Algebraic Discrete Methods 8(2), 277–284 (1987)MathSciNetCrossRefMATHGoogle Scholar
  3. 3.
    Aschinger, M., Drescher, C., Gottlob, G., Jeavons, P., Thorstensen, E.: Structural decomposition methods and what they are good for. In: Proc. STACS. LIPIcs, vol. 9, pp. 12–28. Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)Google Scholar
  4. 4.
    Bliem, B., Morak, M., Woltran, S.: D-FLAT: Declarative problem solving using tree decompositions and answer-set programming. TPLP 12(4-5), 445–464 (2012)MathSciNetMATHGoogle Scholar
  5. 5.
    Bliem, B., Pichler, R., Woltran, S.: Declarative dynamic programming as an alternative realization of courcelle’s theorem. In: Gutin, G., Szeider, S. (eds.) IPEC 2013. LNCS, vol. 8246, pp. 28–40. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  6. 6.
    Bodlaender, H.L.: A tourist guide through treewidth. Acta Cybern. 11(1-2), 1–22 (1993)MathSciNetMATHGoogle Scholar
  7. 7.
    Bodlaender, H.L.: A linear-time algorithm for finding tree-decompositions of small treewidth. SIAM J. Comput. 25(6), 1305–1317 (1996)MathSciNetCrossRefMATHGoogle Scholar
  8. 8.
    Bodlaender, H.L.: Discovering treewidth. In: Vojtáš, P., Bieliková, M., Charron-Bost, B., Sýkora, O. (eds.) SOFSEM 2005. LNCS, vol. 3381, pp. 1–16. Springer, Heidelberg (2005)Google Scholar
  9. 9.
    Bodlaender, H.L., Koster, A.M.C.A.: Combinatorial optimization on graphs of bounded treewidth. Comput. J. 51(3), 255–269 (2008)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Bodlaender, H.L., Koster, A.M.C.A.: Treewidth computations I. Upper bounds. Inf. Comput. 208(3), 259–275 (2010)MathSciNetCrossRefMATHGoogle Scholar
  11. 11.
    Brewka, G., Eiter, T., Truszczyński, M.: Answer set programming at a glance. Commun. ACM 54(12), 92–103 (2011)CrossRefGoogle Scholar
  12. 12.
    Chandra, A.K., Kozen, D., Stockmeyer, L.J.: Alternation. J. ACM 28(1), 114–133 (1981)MathSciNetCrossRefMATHGoogle Scholar
  13. 13.
    Dermaku, A., Ganzow, T., Gottlob, G., McMahan, B., Musliu, N., Samer, M.: Heuristic methods for hypertree decomposition. In: Gelbukh, A., Morales, E.F. (eds.) MICAI 2008. LNCS (LNAI), vol. 5317, pp. 1–11. Springer, Heidelberg (2008)Google Scholar
  14. 14.
    Downey, R.G., Fellows, M.R.: Parameterized Complexity. Monographs in Computer Science. Springer (1999)Google Scholar
  15. 15.
    Gebser, M., Kaminski, R., Kaufmann, B., Ostrowski, M., Schaub, T., Thiele, S.: A user’s guide to gringo, clasp, clingo, and iclingo. Preliminary Draft (2010), http://potassco.sourceforge.net
  16. 16.
    Gebser, M., Kaminski, R., Kaufmann, B., Schaub, T.: Answer Set Solving in Practice. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers (2012)Google Scholar
  17. 17.
    Gelfond, M., Leone, N.: Logic programming and knowledge representation – the A-Prolog perspective. Artif. Intell. 138(1-2), 3–38 (2002)MathSciNetCrossRefMATHGoogle Scholar
  18. 18.
    Gelfond, M., Lifschitz, V.: Classical negation in logic programs and disjunctive databases. New Generation Comput. 9(3/4), 365–386 (1991)CrossRefGoogle Scholar
  19. 19.
    Gottlob, G., Leone, N., Scarcello, F.: Hypertree decompositions and tractable queries. J. Comput. Syst. Sci. 64(3), 579–627 (2002)MathSciNetCrossRefMATHGoogle Scholar
  20. 20.
    Niedermeier, R.: Invitation to Fixed-Parameter Algorithms. Oxford Lecture Series in Mathematics and its Applications. Oxford University Press (2006)Google Scholar
  21. 21.
    Robertson, N., Seymour, P.D.: Graph minors. III. Planar tree-width. J. Comb. Theory, Ser. B 36(1), 49–64 (1984)MathSciNetCrossRefMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Michael Abseher
    • 1
  • Bernhard Bliem
    • 1
  • Günther Charwat
    • 1
  • Frederico Dusberger
    • 1
  • Markus Hecher
    • 1
  • Stefan Woltran
    • 1
  1. 1.Institute of Information Systems 184/2Vienna University of TechnologyViennaAustria

Personalised recommendations