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Abstract

We discuss how to rank one-dimensional fuzzy-rational generalized lotteries of I type – lotteries with continuous real set of prizes, where uncertainty is partially quantifies by p-ribbon distribution functions (CDFs). The p-ribbon CDFs are interpolated on interval quantile estimates of the decision maker. We utilize the Hurwiczα criterion under strict uncertainty to approximate the p-ribbon distribution functions into classical ones. That allows us to transform p-fuzzy rational generalized lotteries of I type into classical ones and use Hurwiczα expected utility principle to rank those. Since the Hurwiczα method weighs the extreme pessimism and extreme optimism, we need to first approximate the p-ribbon distribution functions using the Wald and maximax criteria under strict uncertainty (representing the extreme pessimism and extreme optimism of the fuzzy rational decision maker) before we use the Hurwiczα criterion. A numerical example demonstrates the procedures.

Item Type:	Conference Publication
Authors/Creators:	Nikolova, N and Mednikarov, B and Dimitrakiev, D and Tenekedjiev, K
Keywords:	ribbon distributions, interval estimates, lotteries, strict uncertainty, expected utility
Journal or Publication Title:	International Conference - Automatics and Informatics '18 - Proceedings
Publisher:	John Atanasoff Society of Automatics and Informatics
ISSN:	1313-1850
Copyright Information:	Copyright 2018 John Atanasoff Society of Automatics and Informatics
Related URLs:	Google Scholar: Nikolova, N Google Scholar: Tenekedjiev, K UTAS Profile: Tenekedjiev, K
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