Ranking discrete outcome alternatives with partially quantified uncertainty

International Journal of General Systems

Volumn 37, Issue 2, 2008, Pages 249-274

  Tenekedjiev, Kiril I ^a   Nikolova, Natalia D ^a  

^a TECHNICAL UNIVERSITY OF VARNA   (Bulgaria)

Author keywords

Expected utility; Fuzzy rationality; Hurwicza criteria; Laplace; Wald

Indexed keywords

APPROXIMATION THEORY; DECISION MAKING; FUZZY SYSTEMS; LAPLACE EQUATION; PROBLEM SOLVING; RISK ANALYSIS;

EXPECTED UTILITY; FUZZY RATIONALITY; WALD;

UNCERTAINTY ANALYSIS;

EID: 41149084968     PISSN: 03081079     EISSN: 15635104     Source Type: Journal    
DOI: 10.1080/03081070701409046     Document Type: Article

References (30)

1. ALVAREZ, D.A., 2006, On the calculation of the bounds of probability of events using infinite random sets. International Journal of Approximate Reasoning, 43, pp. 241-267.
2. ATANASSOV, K., 1999, Intuitionistic fuzzy sets (Heidelberg: Springer-Verlag).
3. ATANASSOV, K., 2002, Elements of intuitionistic fuzzy logics. Part II: Intuitionistic fuzzy modal, logics. Advanced Studies on Contemporary Mathematics, 5(1), pp. 1-13.
4. AUGUSTIN, Th, 2001. On decision making under ambiguous prior and sampling information. In G. De cooman, T. Fine, S. Moral and T. Seidenfeld (Eds.), ISIPTA '01: Proceedings of the Second International Symposium on Imprecise Probabilities and their Applications, Cornell University, Ithaca (NY), Shaker, Maastricht, 9-16, http://www.sipta.org/isipta01/proceedings/048. html.
5. AUGUSTIN, Th, 2005, Generalized basic probability assignments. International Journal of General Systems, 34(4), pp. 451-463.
6. BELL, D.E., RAIFFA, H. and TVERSKY, A., 1988. Descriptive, normative, and prescriptive interactions in decision-making. In Decision making, D.Bell, H.Raiffa and A.Tversky, (Eds.), (Cambridge: Cambridge University Press).
7. BELOHLAVEK, R., KLIR, G., LEWIS, H. III and WAY, E., 2002, On the capability of fuzzy set theory to represent concepts. International Journal of General Systems, 31(6), pp. 569-585.
8. CANO, A. and MORAL, S., 2002, Using probability trees to compute marginals with imprecise probabilities. International Journal of Approximate Reasoning, 29, pp. 1-49.
9. COZMAN, F., 2005, Graphical models for imprecise probabilities. International Journal of Approximate Reasoning, 39, pp. 167-184.
10. FRENCH, S., 1993, Decision Theory: An Introduction to the Mathematics of Rationality (UK: Ellis Horwood).
11. FRENCH, S. and INSUA, D.R., 2000, Statistical Decision Theory (USA: Arnold).
12. KLIR, G., 2001, Foundations of fizzu set teory and fuzzy logic: a historical overview. International Journal of General Systems, 30(2), pp. 91-131.
13. KOZINE, I. and UTKIN, L., 2005, Constructing imprecise probability distributions. International Journal of General Systems, 34(4), pp. 401-408.
14. LAW, A.V., PATHAK, D.S. and MCCORD, M.R., 1998, Health status utility assessment by standard gamble: a comparison of the probability equivalence and the lottery equivalence approaches. Pharmaceutical Research, 15(1), pp. 105-109.
15. MACHINA, M. and SCHMEIDLER, D., 1992, A more robust definition of subjective probability. Econometrica, 60(4), pp. 745-780.
16. NIKOLOVA, N., 2006. Two criteria to rank fuzzy-rational lotteries. International Conference on Automatics and Informatics, 3-6 October 2006, Sofia, Bulgaria, pp. 283-286.
17. NIKOLOVA, N.D., DIMITRAKIEV, D. and TENEKEDJIEV, K., 2004. Fuzzy rationality in the elicitation of subjective probabilities. Proceedings of the Second International IEEE Conference on Intelligent Systems IS'2004 Varna, Bulgaria, vol. III, pp. 27-31.
18. NIKOLOVA, N.D., SHULUS, A., TONEVA, D. and TENEKEMIEV, K., 2005, Fuzzy rationality in quantitative decision analysis. JACIII, 9(1), pp. 65-69.
19. PRATT, J.W., RAIFFA, H. and SCHLAIFER, R., 1995, Introduction to Statistical Decision Theory (Cambridge, Massachusetts: MIT Press).
20. PRESS, W.H., TEUKOLSKY, S.A., VETTERLING, W.T. and FLANNERY, B.P., 2002, Numerical Recipes in C++ - the Art of Scientific Computing (Cambridge: Cambridge University Press).
21. QUIGGIN, J., 1993, Generalized Expected Utility Theory - the Rank-Dependent Model (Dordrecht: Kluwer Academic Publishers).
22. RAPOPORT, A., 1989, Decision Theory and Decision Behaviour - Normative and Descriptive Approaches (USA: Kluwer Academic Publishers).
23. SHAFER, G., GILLETT, P. and SCHERL, R., 2003, A new understanding of subjective probability and its generalization to lower and upper prevision. International Journal of Approximate Reasoning, 33, pp. 1-49.
24. SZMIDT, E. and KACPRZYK, J., 1998, Intuitionistic fuzzy linguistic quantifiers. Notes on IFS, 3(5), pp. 111-122.
25. SZMIDT, E. and KACPRZYK, J., 1999. Probability of intuitionistic fuzzy events and their application in decision making. EUSFLAT-ESTYLF Joint Conference, 22-25 September, Palma De Majorca, Spain, pp. 457-460.
26. TENEKEDJIEV, K., 2006. Hurwicz-α expected utility criterion for decisions with partially quantified uncertainty. First International Workshop on Intuitionistic Fuzzy Sets, Generalized Nets and Knowledge Engineering 2-4 September, London, UK, 2006, pp. 56-75.
27. TENEKEDJIEV, K., NIKOLOVA, N.D., KOBASHIKAWA, C. and HIROTA, K., 2006. Conservative betting on sport games with intuitionistic fuzzy described uncertainty. Third International IEEE Conference on Intelligent Systems IS'2006 2-4 September, London, UK, 2006, pp. 747-754.
28. TVERSKY, A. and KAHNEMAN, D., 1992, Advances in prospect theory: cumulative representation of uncertainty. Journal of Risk and Uncertainty, 55, pp. 297-323.
29. ZADEH, L., 1965, Fuzzy sets. Information Control, 8, pp. 338-353.
30. ZADEH, L., 1968, Probability measures of fuzzy events. Journal of Mathematical Analysis and Applications, 23, pp. 421-427.