Abstract
It is widely accepted that a common precept for the choice under uncertainty is to use the expected utility maximization principle, which was established axiomatically. Recently, a formal equivalence between this principle of choice and the target-based principle, that suggests that one should select an action which maximizes the (expected) probability of meeting a (probabilistic) uncertain target, has been established and extensively discussed. In this paper, we discuss the issue of how to bring fuzzy targets within the reach of the target-based model for a class of decision making under uncertainty problems. Two methods for inducing utility functions from fuzzy targets are discussed and illustrated with an example taken from the literature.
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Huynh, VN., Nakamori, Y., Ho, TB. (2006). Utility Function Induced by Fuzzy Target in Probabilistic Decision Making. In: Greco, S., et al. Rough Sets and Current Trends in Computing. RSCTC 2006. Lecture Notes in Computer Science(), vol 4259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11908029_32
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DOI: https://doi.org/10.1007/11908029_32
Publisher Name: Springer, Berlin, Heidelberg
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