K. Bauters, S. Schockaert, M. D. Cock, and D. Vermeir, Semantics for possibilistic answer set programs: Uncertain rules versus rules with uncertain conclusions, International Journal of Approximate Reasoning, vol.55, issue.2, pp.739-761, 2014.
DOI : 10.1016/j.ijar.2013.09.006

K. Bauters, S. Schockaert, M. D. Cock, and D. Vermeir, Characterizing and extending answer set semantics using possibility theory. Theory and Practice of Logic Programming, pp.79-116, 2015.

R. Confalonieri, J. C. Nieves, M. Osorio, and J. Vázquez-salceda, Dealing with explicit preferences and uncertainty in answer set programming, Annals of Mathematics and Artificial Intelligence, vol.5, issue.2, pp.159-198, 2012.
DOI : 10.1007/s10472-012-9311-0

D. Dubois, J. Lang, and H. Prade, Possibilistic logic, Handbook of Logic in Artificial Intelligence and Logic Programming, pp.439-513, 1994.
URL : https://hal.archives-ouvertes.fr/hal-01123493

D. Dubois and H. Prade, Generalized Possibilistic Logic, Proceedings of the 5th International Conference on Scalable Uncertainty Management, pp.428-432, 2011.
DOI : 10.1007/978-3-642-23963-2_33

URL : https://hal.archives-ouvertes.fr/hal-01287713

D. Dubois and H. Prade, Possibilistic Logic ??? An Overview, Handbook of the History of Logic, pp.283-342, 2014.
DOI : 10.1016/B978-0-444-51624-4.50007-1

D. Dubois, H. Prade, and S. Schockaert, Stable models in generalized possibilistic logic, Proceedings of the Thirteenth International Conference on Principles of Knowledge Representation and Reasoning, pp.519-529, 2012.

D. Dubois, H. Prade, and S. Schockaert, Reasoning about uncertainty and explicit ignorance in generalized possibilistic logic, Proceedings of the 21st European Conference on Artificial Intelligence, pp.261-266, 2014.

N. Friedman, J. Y. Halpern, and D. Koller, First-order conditional logic for default reasoning revisited, ACM Transactions on Computational Logic, vol.1, issue.2, pp.175-207, 2000.
DOI : 10.1145/359496.359500

M. Gelfond and V. Lifschitz, The stable model semantics for logic programming, Proceedings of the Fifth International Conference and Symposium on Logic Programming, pp.1081-1086, 1988.

J. Y. Halpern, An analysis of first-order logics of probability, Artificial Intelligence, vol.46, issue.3, pp.311-350, 1990.
DOI : 10.1016/0004-3702(90)90019-V

J. Hu, M. Westphal, and S. Wölfl, Towards a new semantics for possibilistic answer sets, Proceedings of the 37th Annual German Conference on AI, pp.159-170

K. Inoue and C. Sakama, Negation as failure in the head, The Journal of Logic Programming, vol.35, issue.1, pp.39-78, 1998.
DOI : 10.1016/S0743-1066(97)10001-2

V. Lifschitz, Minimal belief and negation as failure, Artificial Intelligence, vol.70, issue.1-2, pp.53-72, 1994.
DOI : 10.1016/0004-3702(94)90103-1

V. Lifschitz, Twelve Definitions of a Stable Model, Proceedings of the 24th International Conference on Logic Programming, pp.37-51, 2008.
DOI : 10.1016/0743-1066(93)90041-E

R. C. Moore, Semantical considerations on nonmonotonic logic, Artificial Intelligence, vol.25, issue.1, pp.75-94, 1985.
DOI : 10.1016/0004-3702(85)90042-6

P. Nicolas, L. Garcia, I. Stéphan, and C. Lefèvre, Possibilistic uncertainty handling for answer set programming, Annals of Mathematics and Artificial Intelligence, vol.3, issue.3, pp.139-181, 2006.
DOI : 10.1007/s10472-006-9029-y

D. Pearce, Equilibrium logic, Annals of Mathematics and Artificial Intelligence, vol.85, issue.1???2, pp.3-41, 2006.
DOI : 10.1007/s10472-006-9028-z