Skip to main content
Log in

An answer set programming encoding of Prioritized Removed Sets Revision: application to GIS

  • Published:
Applied Intelligence Aims and scope Submit manuscript

Abstract

Geographical information systems are ones of the most important application areas of belief revision. Recently, Würbel and colleagues (Proceedings of the seventh international conference about principles of knowledge representation and reasoning, KR2000, pp. 505–516, 2000) have applied the so-called “removed sets revision” (RSR) to the problem of assessment of water heights in a flooded valley. The application was partially satisfactory since only a small part of the valley has been handled. This paper goes one step further, and proposes an extension of (RSR) called “Prioritized Removed Sets Revision” (PRSR). We show that (PRSR) performed using answer set programming makes possible to solve a practical revision problem provided by a real application in the framework of geographical information system (GIS). We first show how PRSR can be encoded into a logic program with answer set semantics, we then present an adaptation of the smodels system devoted to efficiently compute the answer sets in order to perform PRSR. The experimental study shows that the answer set programming approach gives better results than previous implementations of RSR and in particular it allows to handle the whole valley. Lastly, some experimental studies comparing our encoding with implementations based on SAT-solvers are also provided.

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

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Alchourron C, Gärdenfors P, Makinson D (1985) On the logic of theory change: partial meet functions for contraction and revision. J Symb Log 50(2):510–530

    Article  MATH  Google Scholar 

  2. Ben-Naim J, Benferhat S, Papini O, Würbel E (2004) An answer set programming approach of prioritized removed sets revision: application to GIS. In: Alferes J, Leite J (eds) Proceedings of JELIA’04, Lisbon, Portugal, September 2004. Lecture notes in artificial intelligence. Logics for AI. Springer, Berlin, pp 604–616

    Google Scholar 

  3. Benferhat S, Cayrol C, Dubois D, Lang J, Prade H (1993) Inconsistency management and prioritized syntax-based entailment. In: Proceedings of IJCAI93, pp 640–645

  4. Brewka G, Niemelä I, Truszczynski M (2003) Answer set optimization. In: Proceedings of eighteenth international joint conference on artificial intelligence (IJCAI’03), pp 867–872

  5. Buccafurri F, Faber W, Leone N (1999) Disjunctive logic programs with inheritance. In: Proceedings of the 1997 international conference on logic programming. MIT Press, Cambridge, pp 79–93

    Google Scholar 

  6. Cayrol C, Lagasquie-Schiex M-C (1994) On the complexity of nonmonotonic entailment in syntax-based approaches. In: Proceedings of the ECAI94 workshop on algorithms, complexity and commonsense reasoning

  7. Cholewinski P, Marek V, Mikitiuk A, Truszczynski M (1999) Computing with default logic. Artif Intell 112:105–146

    Article  MATH  MathSciNet  Google Scholar 

  8. Delgrande JP, Schaub T, Tompits H (2003) A framework for compiling preferences in logic programs. Theory Pract Log Program 3(2):129–187

    Article  MATH  MathSciNet  Google Scholar 

  9. Doyle J (1979) A truth maintenance system. Artif Intell 12:231–272

    Article  MathSciNet  Google Scholar 

  10. Eén N, Sörensson N (2003) An extensible SAT-solver. In: Proceedings of 6th international conference on theory and applications of satisfiability testing

  11. Eiter T, Gottlob G (1992) On the complexity of propositional knowledge base revision, updates and counterfactual. Artif Intell 57:227–270

    Article  MATH  MathSciNet  Google Scholar 

  12. Eiter T, Leone N, Mateis C, Pfeifer G, Scarcello F (1998) The kr system dlv: progress report, comparison and benchmarks. In: Proceedings of KR’98, pp 406–417

  13. Fagin R, Ullman JD, Vardi MY (1983) On the semantic of updates in databases. In: Proceedings of the 2nd ACM symp. on principles of data base systems, pp 352–365

  14. Gärdenfors P (1988) Knowledge in flux: modeling the dynamics of epistemic states. Bradford books. MIT Press, Cambridge

    Google Scholar 

  15. Gelfond M, Lifschitz V (1988) The stable model semantics for logic programming. In: Proceedings of the international conference on logic programming, pp 1070–1080

  16. Katsuno H, Mendelzon A (1991) Propositional knowledge base revision and minimal change. Artif Intell 52:263–294

    Article  MATH  MathSciNet  Google Scholar 

  17. De Kleer J (1986) An assumption-based TMS. Artif Intell 28:127–162

    Article  Google Scholar 

  18. De Kleer J (1990) Using crude probability estimates to guide diagnosis. Artif Intell 45:381–392

    Article  Google Scholar 

  19. Lehman D (1995) Belief revision revisited. In: Proceedings of 14th int. joint conference on artificial intelligence, pp 1534–1539

  20. Liberatore P, Schaerf M (1996) The complexity of model checking for belief revision and update. In: AAAI’96, pp 556–561

  21. Linke T (2002) More on nomore. In: Proceedings of NMR’02

  22. Nebel B (1991) Belief revision and default reasoning: syntax-based approach. In: Proceedings of knowledge representation, pp 417–427

  23. Nebel B (1998) How hard is to revise a belief base? In: Handbook of defeasible reasoning and uncertainty management systems, vol 3, pp 77–145

  24. Niemelä I (1998) Logic programs with stable semantics as a constraint programming paradigm. In: Proceedings of the workshop on computational aspect of non monotonic reasoning, pp 72–79

  25. Niemelä I, Simons P (1997) An implementation of stable model and well-founded semantics for normal logic programs. In: Proceedings of LPNMR’97, pp 420–429

  26. Osorio M, Zepeda C (2007) Properties of update sequences. In: Proceedings of 4th international workshop on answer set programming (ASP2007)

  27. Papini O (1992) A complete revision function in propositional calculus. In: Neumann B (ed) Proceedings of ECAI92. Wiley, New York, pp 339–343

    Google Scholar 

  28. Raclot D, Puech C (1998) Photographies aériennes et inondation: globalisation d’informations floues par un système de contraintes pour définir les niveaux d’eau en zone inondée. Rev Int Géomatique 8(1):191–206

    Google Scholar 

  29. Rao P, Sagonas K, Swift, Warren DS, Friere J (1997) Xsb: A system for efficiently computing well-founded semantics. In: Proceedings of LPNMR’97, pp 430–440

  30. Reiter R (1987) A theory of diagnosis from first principles. Artif Intell 32:57–95

    Article  MATH  MathSciNet  Google Scholar 

  31. Sakama C, Inoue K (2000) Prioritized logic programming and its application to commonsense reasoning. Artif Intell 123(1–2):185–222

    Article  MATH  MathSciNet  Google Scholar 

  32. Schaub T, Wang K (2001) A comparative study of logic programs with preference. In: Proceedings of seventeenth international joint conference on artificial intelligence (IJCAI’01), pp 597–602

  33. Simons P (2000) Extending and implementing the stable model semantics. PhD Thesis, Helsinki University of Technology

  34. Simons P, Niemelä I, Soininen T (2002) Extending and implementing the stable model semantics. Artif Intell 138(1–2):181–234

    Article  MATH  Google Scholar 

  35. Sombe L (1994) A glance at revision and updating in knowledge bases. Int J Intell Syst 9:1–27

    Article  MATH  Google Scholar 

  36. Wilkerson RW, Greiner R, Smith BA (1989) A correction to the algorithm in Reiter’s theory of diagnosis. Artif Intell 41:79–88

    Article  MATH  MathSciNet  Google Scholar 

  37. Williams MA, Williams D (1997) A belief revision system for the world wide web. In: Proceedings of the IJCAI workshop of the future of artificial intelligence and the Internet, pp 39–51

  38. Würbel E, Jeansoulin R, Papini O (2000) Revision: an application in the framework of gis. In: Cohn AG, Giunchiglia F, Selman B (eds) Proceedings of the seventh international conference about principles of knowledge representation and reasoning, KR2000, Breckenridge, Colorado, USA, April 2000. Morgan Kaufmann, San Mateo, pp 505–516

    Google Scholar 

  39. Würbel E, Jeansoulin R, Papini O (2001) Spatial information revision: a comparison between 3 approaches. In: Proceedings of the sixth European conference on symbolic and quantitative approaches to reasoning with uncertainty, ECSQARU 2001, Toulouse, France. Springer, Berlin, pp 454–465

    Chapter  Google Scholar 

  40. Zang Y, Foo N (1997) Answer sets for prioritized logic programs. In: Proceedings of the 1997 international logic symposium. MIT Press, Cambridge, pp 69–83

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Eric Würbel.

Additional information

This paper is an extended and a revision of the conference paper: “An answer set programming encoding of prioritized removed sets revision: application to GIS” presented at the JELIA’2004 conference.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Benferhat, S., Ben-Naim, J., Papini, O. et al. An answer set programming encoding of Prioritized Removed Sets Revision: application to GIS. Appl Intell 32, 60–87 (2010). https://doi.org/10.1007/s10489-008-0135-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10489-008-0135-x

Keywords

Navigation