Skip to main content
Springer Nature Link
Log in

Multi-level Algorithm Selection for ASP

  • Conference paper
  • First Online:
Logic Programming and Nonmonotonic Reasoning (LPNMR 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9345))

  • 826 Accesses

Abstract

Automated algorithm selection techniques have been applied successfully to Answer Set Programming (ASP) solvers. ASP computation includes two levels of computation: variable substitution, called grounding, and propositional answer set search, called solving. In this paper we present me-asp \(^{ML}\), an extended ASP system applying algorithm selection techniques to both levels of computation in order to choose the most promising solving strategy. Experiments conducted on benchmarks and solvers of the Fifth ASP Competition shows that me-asp \(^{ML}\) is able to solve more instances than state-of-the-art systems.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    claspfolio has been run with its default setting, and with clasp ver. 3 as a back-end solver. This improved version has been provided by Marius Lindauer, who is thanked.

References

  1. Alviano, M., Dodaro, C., Faber, W., Leone, N., Ricca, F.: WASP: a native ASP solver based on constraint learning. In: Cabalar, P., Son, T.C. (eds.) LPNMR 2013. LNCS, vol. 8148, pp. 54–66. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  3. Balduccini, M.: Learning and using domain-specific heuristics in ASP solvers. AI Commun. 24(2), 147–164 (2011)

    MATH  MathSciNet  Google Scholar 

  4. Bomanson, J., Janhunen, T.: Normalizing cardinality rules using merging and sorting constructions. In: Cabalar, P., Son, T.C. (eds.) LPNMR 2013. LNCS, vol. 8148, pp. 187–199. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  5. Calimeri, F., Faber, W., Gebser, M., Ianni, G., Kaminski, R., Krennwallner, T., Leone, N., Ricca, F., Schaub, T.: Asp-core-2 input language format (since 2013). https://www.mat.unical.it/aspcomp2013/ASPStandardization

  6. Calimeri, F., Gebser, M., Maratea, M., Ricca, F.: The design of the fifth answer set programming competition. ICLP 2014 TC abs/1405.3710 (2014). http://arxiv.org/abs/1405.3710

  7. Drescher, C., Gebser, M., Grote, T., Kaufmann, B., König, A., Ostrowski, M., Schaub, T.: Conflict-driven disjunctive answer set solving. In: Proceedings of KR 2008, pp. 422–432. AAAI Press (2008)

    Google Scholar 

  8. Eiter, T., Gottlob, G., Mannila, H.: Disjunctive datalog. ACM TODS 22(3), 364–418 (1997)

    Article  Google Scholar 

  9. Frank, E., Witten, I.H.: Generating accurate rule sets without global optimization. In: ICML 1998, p. 144. Morgan Kaufmann Publisher (1998)

    Google Scholar 

  10. Gebser, M., Janhunen, T., Rintanen, J.: Answer set programming as sat modulo acyclicity. In: Proceedings of ECAI 2014, FAIA, vol. 263, pp. 351–356. IOS Press (2014)

    Google Scholar 

  11. Gebser, M., Kaminski, R., Kaufmann, B., Schaub, T., Schneider, M.T., Ziller, S.: A portfolio solver for answer set programming: preliminary report. In: Delgrande, J.P., Faber, W. (eds.) LPNMR 2011. LNCS, vol. 6645, pp. 352–357. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  12. Gebser, M., Schaub, T., Thiele, S.: GrinGo: a new grounder for answer set programming. In: Baral, C., Brewka, G., Schlipf, J. (eds.) LPNMR 2007. LNCS (LNAI), vol. 4483, pp. 266–271. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  13. Gelfond, M., Lifschitz, V.: Classical negation in logic programs and disjunctive databases. NGC 9, 365–385 (1991)

    Article  Google Scholar 

  14. Hoos, H., Kaminski, R., Lindauer, M.T., Schaub, T.: ASPeed: solver scheduling via answer set programming. TPLP 15(1), 117–142 (2015)

    Google Scholar 

  15. Hoos, H., Lindauer, M.T., Schaub, T.: claspfolio 2: Advances in algorithm selection for answer set programming. TPLP 14(4–5), 569–585 (2014)

    MATH  Google Scholar 

  16. Janhunen, T.: Some (in)translatability results for normal logic programs and propositional theories. J. Appl. Non Class. Logics 16, 35–86 (2006)

    Article  MATH  MathSciNet  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  18. Maratea, M., Pulina, L., Ricca, F.: Automated selection of grounding algorithm in answer set programming. In: Baldoni, M., Baroglio, C., Boella, G., Micalizio, R. (eds.) AI*IA 2013. LNCS, vol. 8249, pp. 73–84. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  19. Maratea, M., Pulina, L., Ricca, F.: A multi-engine approach to answer-set programming. TPLP 14(6), 841–868 (2014)

    MathSciNet  Google Scholar 

  20. Nguyen, M., Janhunen, T., Niemelä, I.: Translating answer-set programs into bit-vector logic. In: Tompits, H., Abreu, S., Oetsch, J., Pührer, J., Seipel, D., Umeda, M., Wolf, A. (eds.) INAP/WLP 2011. LNCS, vol. 7773, pp. 91–109. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  21. Silverthorn, B., Lierler, Y., Schneider, M.: Surviving solver sensitivity: an ASP practitioner’s guide. In: ICLP 2012, LIPIcs, vol. 17, pp. 164–175 (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. DIBRIS, Univ. degli Studi di Genova, Viale F. Causa 15, 16145, Genova, Italy

    Marco Maratea

  2. POLCOMING, Univ. degli Studi di Sassari, Viale Mancini 5, 07100, Sassari, Italy

    Luca Pulina

  3. Dip. di Matematica ed Informatica, Univ. della Calabria, Via P. Bucci, 87030, Rende, Italy

    Francesco Ricca

Authors
  1. Marco Maratea
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Luca Pulina
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Francesco Ricca
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marco Maratea .

Editor information

Editors and Affiliations

  1. University of Calabria, Rende, Italy

    Francesco Calimeri

  2. University of Calabria, Rende, Italy

    Giovambattista Ianni

  3. University of Kentucky Dept. Computer Science, Lexington, Kentucky, USA

    Miroslaw Truszczynski

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Maratea, M., Pulina, L., Ricca, F. (2015). Multi-level Algorithm Selection for ASP. In: Calimeri, F., Ianni, G., Truszczynski, M. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2015. Lecture Notes in Computer Science(), vol 9345. Springer, Cham. https://doi.org/10.1007/978-3-319-23264-5_36

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-23264-5_36

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23263-8

  • Online ISBN: 978-3-319-23264-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation