Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-10T21:15:49.315Z Has data issue: false hasContentIssue false
  • English
  • Français

Query answering in resource-based answer set semantics*

Published online by Cambridge University Press:  14 October 2016

STEFANIA COSTANTINI  and
ANDREA FORMISANO
STEFANIA COSTANTINI
Affiliation:
DISIM, Università di L'Aquila (e-mail: stefania.costantini@univaq.it)
ANDREA FORMISANO
Affiliation:
DMI, Università di Perugia — GNCS-INdAM (e-mail: formis@dmi.unipg.it)
Get access Rights & Permissions [Opens in a new window]

Abstract

In recent work we defined resource-based answer set semantics, which is an extension to answer set semantics stemming from the study of its relationship with linear logic. In fact, the name of the new semantics comes from the fact that in the linear-logic formulation every literal (including negative ones) were considered as a resource. In this paper, we propose a query-answering procedure reminiscent of Prolog for answer set programs under this extended semantics as an extension of XSB-resolution for logic programs with negation.1 We prove formal properties of the proposed procedure. Under consideration for acceptance in TPLP.

Keywords

Answer Set ProgrammingProcedural SemanticsTop-down Query-answering
Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 16 , Special Issue 5-6: 32nd International Conference on Logic Programming , September 2016 , pp. 619 - 635
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

This research is partially supported by YASMIN (RdB-UniPG2016/17) and FCRPG.2016.0105.021 projects.

References

Apt, K. R. and Bol, R. N. 1994. Logic programming and negation: A survey. J. Log. Prog. 19/20, 9–71.Google Scholar
Baral, C. 2003. Knowledge representation, reasoning and declarative problem solving. Cambridge University Press, New York, NY, USA.Google Scholar
Bonatti, P. A., Pontelli, E. and Son, T. C. 2008. Credulous resolution for answer set programming. In Proc. of AAAI 2008, Fox, D. and Gomes, C. P., Eds. AAAI Press, 418–423.Google Scholar
Calimeri, F., Gebser, M., Maratea, M. and Ricca, F. 2016. Design and results of the fifth answer set programming competition. Artif. Intell. 231, 151–181.Google Scholar
Chen, W. and Warren, D. S. 1993. A goal-oriented approach to computing the well-founded semantics. J. Log. Prog. 17, 2/3&4, 279–300.CrossRefGoogle Scholar
Costantini, S. and Formisano, A. 2010. Answer set programming with resources. J. of Logic and Computation 20, 2, 533–571.Google Scholar
Costantini, S. and Formisano, A. 2011. Weight constraints with preferences in ASP. In Proc. of LPNMR'11. LNCS, vol. 6645. Springer, Vancouver, Canada, 229–235.Google Scholar
Costantini, S. and Formisano, A. 2013. RASP and ASP as a fragment of linear logic. J. of Applied Non-Classical Logics 23, 1–2, 49–74.Google Scholar
Costantini, S. and Formisano, A. 2014. Query answering in resource-based answer set semantics. In Proc. of the 29th Italian Conference on Computational Logic. CEUR, Torino, Italy. Also appeared in the 7th Workshop ASPOCP 2014.Google Scholar
Costantini, S. and Formisano, A. 2015. Negation as a resource: a novel view on answer set semantics. Fundam. Inform. 140, 3–4, 279–305.Google Scholar
Costantini, S. and Formisano, A. 2016. Online supplementary materials for “Query Answering in Resource-Based Answer Set Semantics”. TPLP archives. See also the arXiv version in http://arxiv.org/abs/1608.01604, CoRR.Google Scholar
Dix, J. 1995. A classification theory of semantics of normal logic programs I-II. Fundam. Inform. 22, 3, 227–255 and 257–288.Google Scholar
Faber, W., Leone, N. and Pfeifer, G. 2011. Semantics and complexity of recursive aggregates in answer set programming. Artificial Intelligence 175, 1, 278–298.Google Scholar
Gebser, M., Gharib, M., Mercer, R. E. and Schaub, T. 2009. Monotonic answer set programming. J. Log. Comput. 19, 4, 539–564.Google Scholar
Gebser, M. and Schaub, T. 2006. Tableau calculi for answer set programming. In Proc. of ICLP 2006, Etalle, S. and Truszczyński, M., Eds. LNCS, vol. 4079. Springer, Seattle, USA, 11–25.Google Scholar
Gelfond, M. 2007. Answer sets. In Handbook of Knowledge Representation. Chapter 7. Elsevier, Amsterdam, The Netherlands, 285–316.Google Scholar
Gelfond, M. and Lifschitz, V. 1988. The stable model semantics for logic programming. In Proc. of the 5th Intl. Conf. and Symposium on Logic Programming, Kowalski, R. and Bowen, K., Eds. MIT Press, Seattle, USA, 1070–1080.Google Scholar
Giunchiglia, E., Leone, N. and Maratea, M. 2008. On the relation among answer set solvers. Ann. Math. Artif. Intell. 53, 1–4, 169–204.Google Scholar
Lin, F. and You, J. 2002. Abduction in logic programming: A new definition and an abductive procedure based on rewriting. Artificial Intelligence 140, 1/2, 175–205.Google Scholar
Lloyd, J. W. 1993. Foundations of Logic Programming, 2nd ed. Springer, New York, USA.Google Scholar
Marek, V. W. and Truszczyński, M. 1991a. Autoepistemic logic. J. of the ACM 38, 3, 587–618.Google Scholar
Marek, V. W. and Truszczyński, M. 1991b. Computing intersection of autoepistemic expansions. In Proc. LPNMR 1991. MIT Press, Washington, D.C., USA, 35–70.Google Scholar
Marek, V. W. and Truszczyński, M. 1993. Reflective autoepistemic logic and logic programming. In Proc. of LPNMR 1993, Nerode, A. and Pereira, L.M., Eds. The MIT Press, 115–131.Google Scholar
Marek, V. W. and Truszczyński, M. 1999. Stable logic programming - an alternative logic programming paradigm. Springer, Berlin, Heidelberg, 375–398.Google Scholar
Marple, K. and Gupta, G. 2014. Dynamic consistency checking in goal-directed answer set programming. Theory and Practice of Logic Programming 14, 4–5, 415–427.Google Scholar
Simons, P., Niemelä, I. and Soininen, T. 2002. Extending and implementing the stable model semantics. Artificial Intelligence 138, 1–2, 181–234.Google Scholar
Swift, T. and Warren, D. S. 2012. XSB: Extending Prolog with tabled logic programming. Theory and Practice of Logic Programming 12, 1–2, 157–187.CrossRefGoogle Scholar
Truszczyński, M. 2007. Logic programming for knowledge representation. In Logic Programming, 23rd Intl. Conference, ICLP 2007, Dahl, V. and Niemelä, I., Eds. Springer, 76–88.Google Scholar
Van Gelder, A., Ross, K. A. and Schlipf, J. S. 1991. The well-founded semantics for general logic programs. J. ACM 38, 3, 620–650.Google Scholar
Supplementary material: PDF

Costantini and Formisano supplementary material

Costantini and Formisano supplementary material 1

Download Costantini and Formisano supplementary material(PDF)
PDF 163.4 KB