The standard framework of decision theory has no answer to the question how to deal with partial or fuzzy information. In this article two frameworks are presented and compared. The first one uses fuzzy probabilities as in [Buckley 2003] and has been developed by Dubois/Prade [Dubois 1979]. The data-based case is added here. The second framework deals with imprecise probabilities as in [Walley 1991] and proposes a model similar to that by [Kofler 1976]. Furthermore the two frameworks are compared with classical statistical decision theory. It is shown that both of them are similar concerning the mathematical techniques they require but are different regarding the knowledge the decision maker has about the probabilities.
Keywords. decision making, fuzzy probabilities, imprecise probabilities
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| Sven-Hendrik Lossin | losso@web.de |