Rules and meta-rules in the framework of possibility theory and possibilistic logic

Scientia Iranica

Volumn 18, Issue 3 D, 2011, Pages 566-573

  Dubois, D ^a   Prade, H ^a   Schockaert, S ^b  

^a UNIVERSITÉ DE TOULOUSE   (France)

^b GHENT UNIVERSITY   (Belgium)

Author keywords

Fuzzy rule; Meta rule; Possibilistic logic; Possibility theory; Rule

Indexed keywords

COMPUTER CIRCUITS; FUZZY INFERENCE; FUZZY RULES; LOGIC PROGRAMMING;

ANSWER SET PROGRAMMING; EPISTEMIC STATE; HUMAN REASONING; META RULES; PARTIAL SPECIFICATIONS; POSSIBILISTIC LOGIC; POSSIBILITY THEORY; RULE;

FUZZY LOGIC;

FUZZY MATHEMATICS; LOGIT ANALYSIS; META-ANALYSIS; NUMERICAL MODEL;

EID: 80054077000     PISSN: 10263098     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.scient.2011.04.008     Document Type: Article

References (38)

1. Zadeh, LA. "Outline of a new approach to the analysis of complex systems and decision processes", IEEE Trans. Systems, Man and Cybernetics, 3, pp. 28-44 (1973).
2. Zadeh, LA. "Fuzzy sets as a basis for a theory of possibility". Fuzzy Sets and Systems, 1, pp. 3-28 (1978).
3. Zadeh, LA. "PRUF-A meaning representation language for natural languages", Int. J. of Man-Machine Studies, 10, pp. 395-460 (1978).
4. Zadeh, LA. "A theory of approximate reasoning", In Machine Intelligence, 9, J.E. Hayes, D. Michie and Li. Mikulich, Eds., pp. 149-194, Elsevier, Amsterdam, The Netherlands (1979).
5. Zadeh, LA. "Thinking machines. A new field in electrical engineering", Columbia Engineering Quarterly, 3,12-13 & 30-31 (1950).
6. Dubois, D., Lang, J. and Prade, H. "Automated reasoning using possibilistic logic: semantics, belief revision and variable certainty weights", IEEE Trans. on Data and Knowledge Engineering, 6 (1), pp. 64-71 (1994).
7. Dubois, D., Lang, J. and Prade, H. "Possibilistic logic", In Handbook of Logic in Artificial Intelligence and Logic Programming, 3, D.M. Gabbay, CJ. Hogger, J.A. Robinson and D. Nute, Eds., pp. 439-513, Oxford University Press, UK(1994).
8. Dubois, D. and Prade, H. "Possibilistic logic: a retrospective and prospective view", Fuzzy Sets and Systems, 144, pp. 3-23 (2004).
9. Dubois, D., Lang, J. and Prade, H. "Fuzzy sets in approximate reasoning. Part Logical approaches", Fuzzy Sets and Systems, 40, pp. 203-244 (1991) .
10. Dubois, D. and Prade, H. Possibilistic logic, preferential models, non-monotonicity and related issues, Proc. of the Inter. Joint Conf. on Artificial Intelligence (1JCAV91), Sydney, pp. 419-424 (1991).
11. Benferhat, S., Dubois, D. and Prade, H. "Nonmonotonic reasoning, conditional objects and possibility theory", Artificial Intelligence, 92, pp. 259-276 (1997).
12. Benferhat, S., Dubois, D. and Prade, H. "Practical handling of exceptiontainted rules and independence information in possibilistic logic", Applied Intelligence, 9, pp. 101-127 (1998).
13. Schockaert, S., De Cock, M. and Kerre, E., Reasoning about Fuzzy Temporal and Spatial Information from the Web, World Scientific, Singapore (2011).
14. Zadeh, LA. "The calculus of fuzzy if-then rules", Al Expert, 7(3), pp. 23-27(1992).
15. Zadeh, LA. "Fuzzy logic, neural networks, and soft computing". Communications of the ACM, 37(3), pp. 77-84 (1994).
16. Zadeh, LA. "Toward a theory of fuzzy systems", In Aspects of Networks and Systems Theory, R.E. Kaiman and N. De Claris, Eds., pp. 469-490, Rinehart and Winston, New York Holt (1971) .
17. Zadeh, LA. "On the analysis of large scale systems", In Systems Approaches and Environment Problems, H. Gottinger, Ed., pp. 23-37, Vandenhoeck and Ruprecht, Gottingen, Germany (1974).
18. Mamdani, E.H. and Assilian, S. "An experiment in linguistic synthesis with a fuzzy logic controller", International Journal on Man-Machine Studies, 7, pp. 1-13(1975).
19. Anderson, A.R. and Belnap, N.D. Entailment. The Logic of Relevance and Necessity, I,Princeton University Press (1975); 2, Edited collection with the collaboration of J.M. Dunn, Princeton University Press, 1992.
20. Gardenförs, P., Knowledge in Flux. Modelling the Dynamics of Epistemic States, MIT Press, Cambridge, MA (1988).
21. Zadeh, LA. "Toward a generalized theory of uncertainty (GTU)-principal concepts and ideas". Computational Statistics and Data Analysis, 51, pp. 15-46(2006).
22. Bouchon-Meunier, B., Dubois, D., Godo, L and Prade, H. "Fuzzy sets and possibility theory in approximate and plausible reasoning", In Fuzzy Sets in Approximate Reasoning and Information Systems,j. Bezděk, D. Dubois and H. Prade, Eds., pp. 15-190, Kluwer Acad. Publ., Dordrecht, The Netherlands(1999).
23. |23] Dubois, D. and Prade, H., Possibility Theory, Plenum Press, New-York(1988).
24. Dubois, D. and Prade, H. "Possibility theory: qualitative and quantitative aspects", In Handbook of Defeasible Reasoning and Uncertainty Management Systems, I, D.M. Gabbay and P. Smets, Eds., pp. 169-226, Kluwer Acad. Publ., Dordrecht, The Netherlands (1998).
25. Dubois, D. and Prade, H. "What are fuzzy rules and how to use them". Fuzzy Sets andSystems, 84, pp. 169-185 (1996).
26. Dubois, D., Prade, H. and Ughetto, L "A new perspective on reasoning with fuzzy rules". Inter. J. of Intelligent Systems, 18, pp. 541-567 (2003).
27. Dubois, D. and Prade, H. "Bipolar representations in reasoning, knowledge extraction and decision", In Proc. Inter. Conf. on Rough Sets and Current Trends in Computing(RSCTC2006), Kobe. Japan, S. Greco, Y. Hata, S. Hirano and M. inuiguchi, Eds., In LNAl, vol. 4259, pp. 15-26, Springer, Berlin (2006).
28. Esteva, F., Garcia, P. and Godo, L On the semantics of fuzzy statements based on possibilistic constraints, Proc. VlI Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF97), Tarragona, pp. 21-27 (1997).
29. Cross, V. and Sudkamp, T. "Patterns of fuzzy rule-based inference", Int. J. of Approximate Reasoning, 11, pp. 235-255 (1994).
30. Zadeh, LA. QSA/FL-qualitative systems analysis based on fuzzy logic, Working Notes of the Stanford AAAl Symp. on Al and Limited Rationality, M. Fehling, S. Russell, Eds., pp. 111-114, Stanford, CA (1989).
31. Halpern, J. "Defining relative likelihood in partially-ordered preferential structures", J. of Artificial Intelligence Research, 1, pp. 1-24 (1997).
32. Dubois, D. and Prade, H. Toward multiple-agent extensions of possibilistic logic, Proc. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2007), London, pp. 187-192 (2007).
33. Bauters, K., Schockaert, S., De Cock, M. and Vermeir, D. Possibilistic answer set programming revisited, Proc. 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010), Catalina Island (2010).
34. Nicolas, P., Garcia, L and Stephan, i. Possibilistic stable models, Proc. of the 19th International Joint Conference on Artificial Intelligence (IJCAl 2005), LP. Kaelbling, A. Saffiotti, Eds., Edinburgh, pp. 248-253 (2005).
35. Banerjee, M. and Dubois, D. "A simple modal logic for reasoning about revealed beliefs", In Proc. European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2009), Verona, C. Sossai and G. Chemello, Eds., In LNAI, 5590, pp. 805-816, Springer (2009).
36. Prade, H. Handling (un)awareness and related issues in possibilistic logic: A preliminary discussion, Proc. International Workshop on NonMonotonic Reasoning (NMR 2006), Lake District, UK, Clausthal University of Technology, pp. 219-225 (2006).
37. Dubois, D., Foulloy, L, Galichet, S. and Prade, H. "Performing approximate reasoning with words?", In Computing with Words in Information/Intelligent Systems, I, LA. Zadeh and J. Kacprzyk, Eds., pp. 24-49, Springer-Verlag (1999).
38. Zadeh, LA. "Fuzzy logic = computing with words", IEEE Trans, on Fuzzy Systems, 4, pp. 103-111 (1996).