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Optimizing Answer Set Computation via Heuristic-Based Decomposition

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Practical Aspects of Declarative Languages (PADL 2018)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10702))

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Abstract

Answer Set Programming (ASP) is a purely declarative formalism developed in the field of logic programming and nonmonotonic reasoning. With ASP, computational problems are encoded by logic programs whose answer sets, corresponding to solutions, are computed by an ASP system. In general, several semantically equivalent programs might be defined for the same problem; however, performance of ASP systems while evaluating them might significantly vary. We propose an approach for automatically transforming an input logic program into an equivalent one that can be evaluated more efficiently. To this aim, one can make use of existing tree-decomposition techniques for rewriting selected rules into a set of multiple ones. The idea is to guide and adaptively apply them on the basis of proper new heuristics, in order to obtain a smart rewriting algorithm to be integrated into an ASP system. The method is rather general: it can be adapted to the system at hand and implement different preference policies. Furthermore, we define a set of new heuristics explicitly tailored at optimizing one of the main phases of the typical ASP computation, namely the grounding process; we make use of them in order to actually implement the approach into the ASP system DLV, and in particular into its grounding subsystem \(\mathcal I\)-DLV, and carry out an extensive experimental activity aimed at assessing the impact of the proposal.

This work has been partially supported by the Italian Ministry for Economic Development (MISE) under project “PIUCultura – Paradigmi Innovativi per l’Utilizzo della Cultura” (n. F/020016/01-02/X27), and under project “Smarter Solutions in the Big Data World (S2BDW)” (n. F/050389/01-03/X32) funded within the call “HORIZON2020” PON I&C 2014-2020.

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Notes

  1. 1.

    We remark that this definition of safety is specific for the syntax considered herein. For a complete definition we refer the reader to [8].

  2. 2.

    According to \(\mathsf {ASP\text {-}Core\text {-}2}\) syntax, the term (1..k) stands for all values from 1 to k.

  3. 3.

    https://github.com/mabseher/htd.

  4. 4.

    Experiments have been performed on a NUMA machine equipped with two 2,8GHz AMD Opteron 6320 and 128 GiB of main memory, running Linux Ubuntu 14.04.4 (kernel ver. 3.19.0-25). Binaries have been generated by the GNU C++ compiler 5.4.0. We allotted 15 GiB and 600 s to each system per each single run, as memory and time limits.

References

  1. Abseher, M., Musliu, N., Woltran, S.: htd – a free, open-source framework for (customized) tree decompositions and beyond. In: Salvagnin, D., Lombardi, M. (eds.) CPAIOR 2017. LNCS, vol. 10335, pp. 376–386. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-59776-8_30

    Chapter  Google Scholar 

  2. Alviano, M., et al.: The ASP system DLV2. In: Balduccini, M., Janhunen, T. (eds.) LPNMR 2017. LNCS (LNAI), vol. 10377, pp. 215–221. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61660-5_19

    Chapter  Google Scholar 

  3. Alviano, M., Dodaro, C., Leone, N., Ricca, F.: Advances in WASP. In: Calimeri, F., Ianni, G., Truszczynski, M. (eds.) LPNMR 2015. LNCS (LNAI), vol. 9345, pp. 40–54. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23264-5_5

    Chapter  Google Scholar 

  4. Alviano, M., Faber, W., Greco, G., Leone, N.: Magic sets for disjunctive datalog programs. Artif. Intell. 187, 156–192 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  5. Bichler, M., Morak, M., Woltran, S.: lpopt: a rule optimization tool for answer set programming. In: LOPSTR, pp. 114–130 (2016)

    Google Scholar 

  6. Bliem, B., Moldovan, M., Morak, M., Woltran, S.: The impact of treewidth on ASP grounding and solving. In: Sierra, C. (ed.) IJCAI, pp. 852–858. ijcai.org (2017). http://www.ijcai.org/Proceedings/2017/

  7. Brewka, G., Eiter, T., Truszczynski, M.: Answer set programming at a glance. Commun. ACM 54(12), 92–103 (2011)

    Article  Google Scholar 

  8. Calimeri, F., Faber, W., Gebser, M., Ianni, G., Kaminski, R., Krennwallner, T., Leone, N., Ricca, F., Schaub, T.: Asp-core-2: input language format (2012). https://www.mat.unical.it/aspcomp2013/files/ASP-CORE-2.03b.pdf

  9. Calimeri, F., Fuscà, D., Perri, S., Zangari, J.: The ASP instantiator I-DLV. In: PAoASP, Espoo, Finland (2017)

    Google Scholar 

  10. Calimeri, F., Fuscà, D., Perri, S., Zangari, J.: I-DLV: the new intelligent grounder of DLV. Intelligenza Artificiale 11(1), 5–20 (2017)

    Article  Google Scholar 

  11. Calimeri, F., Fuscà, D., Perri, S., Zangari, J.: \(\cal{I}\)-DLV \(+\cal{MS}\): preliminary report on an automatic ASP solver selector. In: RCRA (2017, to appear)

    Google Scholar 

  12. Calimeri, F., Gebser, M., Maratea, M., Ricca, F.: Design and results of the fifth answer set programming competition. Artif. Intell. 231, 151–181 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  13. Dal Palù, A., Dovier, A., Pontelli, E., Rossi, G.: GASP: answer set programming with lazy grounding. Fundamenta Informaticae 96(3), 297–322 (2009)

    MathSciNet  MATH  Google Scholar 

  14. Dao-Tran, M., Eiter, T., Fink, M., Weidinger, G., Weinzierl, A.: OMiGA: an open minded grounding on-the-fly answer set solver. In: del Cerro, L.F., Herzig, A., Mengin, J. (eds.) JELIA 2012. LNCS (LNAI), vol. 7519, pp. 480–483. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33353-8_38

    Chapter  Google Scholar 

  15. Eiter, T., Kaminski, T., Weinzierl, A.: Lazy-grounding for answer set programs with external source access. In: IJCAI, pp. 1015–1022 (2017)

    Google Scholar 

  16. Gebser, M., Kaminski, R., Kaufmann, B., Romero, J., Schaub, T.: Progress in clasp series 3. In: Calimeri, F., Ianni, G., Truszczynski, M. (eds.) LPNMR 2015. LNCS (LNAI), vol. 9345, pp. 368–383. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23264-5_31

    Chapter  Google Scholar 

  17. Gebser, M., Maratea, M., Ricca, F.: The design of the sixth answer set programming competition. In: Calimeri, F., Ianni, G., Truszczynski, M. (eds.) LPNMR 2015. LNCS (LNAI), vol. 9345, pp. 531–544. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23264-5_44

    Chapter  Google Scholar 

  18. Gebser, M., Maratea, M., Ricca, F.: What’s hot in the answer set programming competition. In: AAAI, pp. 4327–4329 (2016)

    Google Scholar 

  19. Gebser, M., Maratea, M., Ricca, F.: The design of the seventh answer set programming competition. In: Balduccini, M., Janhunen, T. (eds.) LPNMR 2017. LNCS (LNAI), vol. 10377, pp. 3–9. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61660-5_1

    Chapter  Google Scholar 

  20. Gelfond, M., Lifschitz, V.: Classical negation in logic programs and disjunctive databases. New Gener. Comput. 9(3/4), 365–385 (1991). https://doi.org/10.1007/BF03037169

    Article  MATH  Google Scholar 

  21. Gottlob, G., Grohe, M., Musliu, N., Samer, M., Scarcello, F.: Hypertree decompositions: structure, algorithms, and applications. In: Kratsch, D. (ed.) WG 2005. LNCS, vol. 3787, pp. 1–15. Springer, Heidelberg (2005). https://doi.org/10.1007/11604686_1

    Chapter  Google Scholar 

  22. Gottlob, G., Leone, N., Scarcello, F.: Hypertree decompositions: a survey. In: Sgall, J., Pultr, A., Kolman, P. (eds.) MFCS 2001. LNCS, vol. 2136, pp. 37–57. Springer, Heidelberg (2001). https://doi.org/10.1007/3-540-44683-4_5

    Chapter  Google Scholar 

  23. Kaufmann, B., Leone, N., Perri, S., Schaub, T.: Grounding and solving in answer set programming. AI Mag. 37(3), 25–32 (2016)

    Article  Google Scholar 

  24. Lefèvre, C., Nicolas, P.: The first version of a new ASP solver: ASPeRiX. In: Erdem, E., Lin, F., Schaub, T. (eds.) LPNMR 2009. LNCS (LNAI), vol. 5753, pp. 522–527. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-04238-6_52

    Chapter  Google Scholar 

  25. Leone, N., Perri, S., Scarcello, F.: Improving ASP instantiators by join-ordering methods. In: Eiter, T., Faber, W., Truszczyński, M. (eds.) LPNMR 2001. LNCS (LNAI), vol. 2173, pp. 280–294. Springer, Heidelberg (2001). https://doi.org/10.1007/3-540-45402-0_21

    Chapter  Google Scholar 

  26. Leone, N., Pfeifer, G., Faber, W., Eiter, T., Gottlob, G., Perri, S., Scarcello, F.: The DLV system for knowledge representation and reasoning. ACM Trans. Comput. Log. (TOCL) 7(3), 499–562 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  27. Lifschitz, V.: Answer set planning. In: Gelfond, M., Leone, N., Pfeifer, G. (eds.) LPNMR 1999. LNCS (LNAI), vol. 1730, pp. 373–374. Springer, Heidelberg (1999). https://doi.org/10.1007/3-540-46767-X_28

    Chapter  Google Scholar 

  28. Morak, M., Woltran, S.: Preprocessing of complex non-ground rules in answer set programming. In: LIPIcs-Leibniz International Proceedings in Informatics, vol. 17. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik (2012)

    Google Scholar 

  29. Ullman, J.D.: Principles of Database and Knowledge-Base Systems, vol. I. Computer Science Press, New York (1988)

    Google Scholar 

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Calabria, Rende, Italy

    Francesco Calimeri, Davide Fuscà, Simona Perri & Jessica Zangari

  2. DLVSystem Srl, Rende, Italy

    Francesco Calimeri

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  1. Francesco Calimeri
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  2. Davide Fuscà
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  3. Simona Perri
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  4. Jessica Zangari
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Correspondence to Jessica Zangari .

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Editors and Affiliations

  1. Department of Mathematics and Computer Science, University of Calabria, Rende, Italy

    Francesco Calimeri

  2. Computer Science Department, University of Texas at Dallas, Richardson, Texas, USA

    Kevin Hamlen

  3. Department of Mathematics and Computer Science, University of Calabria, Rende, Italy

    Nicola Leone

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Calimeri, F., Fuscà, D., Perri, S., Zangari, J. (2018). Optimizing Answer Set Computation via Heuristic-Based Decomposition. In: Calimeri, F., Hamlen, K., Leone, N. (eds) Practical Aspects of Declarative Languages. PADL 2018. Lecture Notes in Computer Science(), vol 10702. Springer, Cham. https://doi.org/10.1007/978-3-319-73305-0_9

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  • DOI: https://doi.org/10.1007/978-3-319-73305-0_9

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