From ordered beliefs to numbers: How to elicit numbers without asking for them (Doable but computationally difficult)

International Journal of Intelligent Systems

Volumn 13, Issue 9, 1998, Pages 801-820

  Cloteaux, Brian ^a,d   Eick, Christoph ^b   Bouchon Meunier, Bernadette ^c   Kreinovich, Vladik ^a  

^a 500 W University Avenue   (United States)

^b University of Houston   (United States)

^c UNIVERSITÉ PIERRE ET MARIE CURIE   (France)

^d EXXONMOBIL UPSTREAM RESEARCH COMPANY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; COMPUTER SYSTEMS PROGRAMMING; KNOWLEDGE ACQUISITION; KNOWLEDGE REPRESENTATION; NUMBER THEORY; PROBLEM SOLVING;

DEGREES OF BELIEF;

EXPERT SYSTEMS;

EID: 0032165949     PISSN: 08848173     EISSN: None     Source Type: Journal    
DOI: 10.1002/(SICI)1098-111X(199809)13:9<801::AID-INT2>3.0.CO;2-M     Document Type: Article

References (17)

1. B. Bouchon-Meunier and V. Kreinovich, "Simulating fuzzy control as a new method of eliciting membership functions," Proc. Int. Conf. on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU'96), Granada, Spain, July 1-5, 1996, pp. 1049-1054.
2. C. Boutilier, "Conditional logics of normality: a modal approach," Artificial Intell., 68, 87-154 (1994).
3. L.S. Chee, "Computing the value of a Boolean expression with interval inputs is NP-hard," Reliable Comput., 3, 155-172 (1997).
4. D. Dubois and H. Prade, Possibility Theory - An Approach to Computerized Processing of Uncertainty, Plenum, New York, 1988.
5. C.F. Eick and N.M. Mehta, "Decision blocks - a tool for rule-based decision making involving imperfect knowledge," IEEE Trans. Syst. Man, Cybernetics, 23, 840-850 (1993).
6. M.R. Garey and D.S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness, Freeman, San Francisco, 1979.
7. N. Karmarkar, "A new polynomial-time algorithm for linear programming," Combinatorica, 4, 373-396 (1984).
8. L.G. Khachiyan, "A polynomial-time algorithm for linear programming," Sov. Math. Dokl., 20, 191-194 (1979).
9. G. Klir and B. Yuan, Fuzzy Sets and Fuzzy Logic: Theory and Applications, Prentice-Hall, Englewood Cliffs, NJ, 1995.
10. V. Kreinovich, H.T. Nguyen, and E.A. Walker, "Maximum entropy (Max-Ent) method in expert systems and intelligent control: New possibilities and limitations," in Maximum Entropy and Bayesian Methods, K.M. Hanson and R.N. Silver, Eds., Kluwer, Dordrecht, 1996, pp. 93-100.
11. X. Ménage and B. Bouchon-Meunier, "Competitive learning of possibility distributions," Proc. Third IEEE Conf. on Fuzzy Systems, IEEE Press, New York, 1994 Vol. I, pp. 442-445.
12. H.T. Nguyen and V. Kreinovich, "Towards theoretical foundations of soft computing applications," Int. J. Uncertainty, Fuzziness, and Knowledge-Based Syst., 3, 341-373 (1995).
13. H.T. Nguyen and E.A. Walker, A First Course in Fuzzy Logic, CRC Press, Boca Raton, FL, 1997.
14. J. Pearl, Probabilistic Reasoning in Intelligent Systems, Morgan Kaufmann, San Mateo, CA, 1988.
15. A. Ramer and V. Kreinovich, "Maximum entropy approach to fuzzy control," Inform. Sci., 81, 235-260 (1994).
16. G. Shafer and J. Pearl, Eds., Readings in Uncertain Reasoning, Morgan Kaufmann, San Mateo, CA, 1990.
17. R.R. Yager, J. Kacprzyk, and M. Pedrizzi, Eds., Advances in the Dempster-Shafer Theory of Evidence, John Wiley, New York, 1994.