Possibilistic stable models

IJCAI International Joint Conference on Artificial Intelligence

Volumn , Issue , 2005, Pages 245-253

  Nicolas, Pascal ^a   Garcia, Laurent ^a   Steṕhan, Igor ^a  

^a UNIVERSITÉ D'ANGERS   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ANSWER SET PROGRAMMING; LOGIC PROGRAMS; NECESSITY MEASURES; POSSIBILISTIC; POSSIBILITY DISTRIBUTIONS; POSSIBILITY THEORY; SEMANTIC PARTS; STABLE MODEL SEMANTICS;

ARTIFICIAL INTELLIGENCE; KNOWLEDGE REPRESENTATION; SEMANTICS; SYNTACTICS;

LOGIC PROGRAMMING;

EID: 84880756140     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. T. Alsinet and L. Godo. A complete calculus for possibilistic logic programming with fuzzy propositional variables. In C. Boutilier and M. Goldszmidt, editors, UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, pages 1-10, Stanford University, Stanford, California, USA, 2000. Morgan Kaufmann.
2. S. Benferhat, D. Dubois, and H. Prade. Possibilistic logic: From nonmonotonicity to logic programming. In M. Clarke, R. Kruse, and S. Moral, editors, European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, volume 747 of LNCS, pages 17-24. Springer, 1993.
3. G. Brewka and T. Eiter. Preferred answer sets for extended logic programs. Artificial Intelligence, 109(1-2):297-356, 1999.
4. C. V. Damasio and L. M. Pereira. Antitonic logic programs. In T. Eiter, W. Faber, and M. Truszczynski, editors, International Conference on Logic Programming and NonMonotonic Reasoning, volume 2173 of LNCS, pages 379-392. Springer, 2001.
5. C. V. Damasio and L. M. Pereira. Monotonic and residuated logic programs. In S. Benferhat and P. Besnard, editors, European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, volume 2143 of LNCS, pages 748-759. Springer, 2001.
6. J. Delgrande, T. Schaub, H. Tompits, and K. Wang. A classification and survey of preference handling approaches in nonmonotonic reasoning. Computational Intelligence, 20(2):308-334, 2004.
7. D. Dubois and H. Prade. Possibility theory: qualitative and quantitative aspects. In Ph. Smets, editor, Handbook of Defeasible Reasoning and Uncertainty Management Systems, volume 1, pages 169-226. Kluwer Academic Press, 1998.
8. D. Dubois, J. Lang, and H. Prade. Towards possibilistic logic programming. In K. Furukawa, editor, International Conference on Logic Programming, pages 581-595, Cambridge, MA, 1991. MIT Press.
9. D. Dubois, J. Lang, and H. Prade. Possibilistic logic. In D. Gabbay, C. Hogger, and J. Robinson, editors, Handbook of Logic in Artificial Intelligence and Logic Programming, volume 3, pages 439-513. Oxford University Press, 1995.
10. T. Eiter, N. Leone, C. Mateis, G. Pfeifer, and F. Scarcello. The kr system dlv:progress report, comparisons and benchmarks. pages 406-417. Morgan Kaufmann Publishers, 1998.
11. M. Gelfond and V. Lifschitz. The stable model semantics for logic programming. In Robert A. Kowalski and Kenneth Bowen, editors, International Conference on Logic Programming, pages 1070-1080. The MIT Press, 1988.
12. M. Gelfond and V. Lifschitz. Classical negation in logic programs and disjunctive databases. New Generation Computing, 9(3-4):363-385, 1991.
13. Y. Loyer and U. Straccia. Default knowledge in logic programs with uncertainty. In International Conference on Logic Programming, volume 2916 of LNCS, pages 466-480, Mumbai, India, 2003. Springer.
14. A. Nerode, J. B. Remmel, and V. S. Subrahmanian. Annotated nonmonotonic rule systems. Theoretical Computer Science, 171(1-2):111-146, 1997. (Pubitemid 127452810)
15. P. Nicolas, L. Garcia, and I. Stéphan. A possibilistic inconsistency handling in answer set programming. In European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, LNCS, Barcelona, Spain, 2005. Springer.
16. I. Niemelä and P. Simons. Smodels - an implementation of the stable model and well-founded semantics for normal logic programs. In International Conference on Logic Programming and NonMonotonic Reasoning, volume 1265 of LNCS, pages 420-429. Springer, 1997.
17. G. Wagner. A logical reconstruction of fuzzy inference in databases and logic programs. In Proc. of Int. Fuzzy Set Association World Congress (IFSA), Prague, Czech, 1997.
18. L.A. Zadeh. Fuzzy sets as a basis for a theory of possibility. In Fuzzy Sets and Systems, volume 1, pages 3-28. 1978.