×

zbMATH — the first resource for mathematics

Justifications and blocking sets in a rule-based answer set computation. (English) Zbl 1428.68090
Carro, Manuel (ed.) et al., Technical communications of the 32nd international conference on logic programming, ICLP 2016, October 16–21, 2016, New York, NY, USA. Wadern: Schloss Dagstuhl – Leibniz Zentrum für Informatik. OASIcs – OpenAccess Ser. Inform. 52, Article 6, 15 p. (2016).
Summary: Notions of justifications for logic programs under answer set semantics have been recently studied for atom-based approaches or argumentation approaches. The paper addresses the question in a rule-based answer set computation: the search algorithm does not guess on the truth or falsity of an atom but on the application or non application of a non monotonic rule. In this view, justifications are sets of ground rules with particular properties. Properties of these justifications are established; in particular the notion of blocking set (a reason incompatible with an answer set) is defined, that permits to explain computation failures. Backjumping, learning, debugging and explanations are possible applications.
For the entire collection see [Zbl 1407.68025].
MSC:
68N17 Logic programming
Software:
ASPeRiX; OMiGA
PDF BibTeX XML Cite
Full Text: DOI
References:
[2] C. V. Damásio, J. Moura, and A. Analyti. Unifying justifications and debugging for answerset programs. In ICLP 2015, 2015.
[3] M. Dao-Tran, T. Eiter, M. Fink, G. Weidinger, and A. Weinzierl. OMiGA: An open minded grounding on-the-fly answer set solver. In JELIA 2012, pages 480-483, 2012.
[4] T. Eiter, M. Fink, P. Schüller, and A. Weinzierl. Finding explanations of inconsistency in multi-context systems. In KR 2010, 2010.
[5] M. Gebser, B. Kaufmann, A. Neumann, and T. Schaub. Conflict-driven answer set solving. In IJCAI 2007, pages 386-392, 2007. · Zbl 1149.68332
[6] :15
[7] M. Gebser, J. Pührer, T. Schaub, and H. Tompits. A meta-programming technique for debugging answer-set programs. In AAAI 2008, pages 448-453, 2008.
[8] M. Gelfond and V. Lifschitz. The stable model semantics for logic programming. In Logic Programming, Proceedings of the Fifth International Conference and Symposium, pages 1070-1080, 1988.
[9] K. Konczak, T. Linke, and T. Schaub.Graphs and colorings for answer set programming.Theory and Practice of Logic Programming, 6:61-106, 1 2006.doi:10.1017/ S1471068405002528. · Zbl 1109.68081
[10] C. Lefèvre, C. Béatrix, I. Stéphan, and L. Garcia. Asperix, a first order forward chaining approach for answer set computing. CoRR, abs/1503.07717:(to appear in TPLP), 2015. URL: http://arxiv.org/abs/1503.07717.
[11] C. Lefèvre and P. Nicolas. A first order forward chaining approach for answer set computing. In LPNMR 2009, pages 196-208, 2009. · Zbl 1258.68033
[12] C. Lefèvre and P. Nicolas. The first version of a new ASP solver : ASPeRiX. In LPNMR 2009, pages 522-527, 2009.
[13] N. Leone, G. Pfeifer, W. Faber, T. Eiter, G. Gottlob, S. Perri, and F. Scarcello. The DLV system for knowledge representation and reasoning. ACM Transactions on Computational Logic, 7(3):499-562, 2006. doi:10.1145/1149114.1149117. · Zbl 1367.68308
[14] L. Liu, E. Pontelli, T. C. Son, and M. Truszczynski. Logic programs with abstract constraint atoms: The role of computations. Artificial Intelligence, 174(3-4):295-315, 2010. doi: 10.1016/j.artint.2009.11.016. · Zbl 1207.68119
[15] J. Oetsch, J. Pührer, and H. Tompits. Stepping through an answer-set program. In LPNMR 2011, pages 134-147, 2011. · Zbl 1327.68068
[16] A. Dal Palù, A. Dovier, E. Pontelli, and G. Rossi. Answer set programming with constraints using lazy grounding. In ICLP 2009, 2009. · Zbl 1207.68118
[17] E. Pontelli, T. C. Son, and O. El-Khatib. Justifications for logic programs under answer set semantics. Theory and Practice of Logic Programming, 9(1):1-56, 2009. doi:10.1017/ S1471068408003633. · Zbl 1170.68005
[18] C. Schulz and F. Toni. Justifying answer sets using argumentation. Theory and Practice of Logic Programming, 16(1):59-110, 2016. doi:10.1017/S1471068414000702.
[19] P. Simons, I. Niemelä, and T. Soininen. Extending and implementing the stable model semantics. Artificial Intelligence, 138(1-2):181-234, 2002. doi:10.1016/S0004-3702(02) 00187-X. · Zbl 0995.68021
[20] A. Weinzierl.Learning non-ground rules for answer-set solving.In 2nd Workshop on Grounding and Transformations for Theories with Variables, GTTV 2013, 2013.
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.