A decision maker has to choose one of several random variables whose distributions are not known. As a Bayesian, she behaves as if she knew the distributions. In this paper we suggest an axiomatic derivation of these (subjective) distributions, which is more economical than the derivations by de Finetti or Savage. Whereas the latter derive the whole joint distribution of all the available random variables, our approach derives only the marginal distributions. Correspondingly, the preference questionnaire needed in our case is less smaller. Copyright Kluwer Academic Publishers 2004
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- Itzhak Gilboa & David Schmeidler & Peter P. Wakker, 2002.
"Utility in Case-Based Decision Theory,"
- Gilboa,Itzhak & Schmeidler,David, 2001.
"A Theory of Case-Based Decisions,"
Cambridge University Press, number 9780521802345, November.
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