A decision maker has to choose one of several random variables, with uncertainty known distributions. As a Bayesian she behaves as if she knew the distributions. In his paper we suggest an axiomatic derivation of these (subjective) distributions, which is much more economical than the derivations by de Finetti or Savage. They derive the whole joint distribution of all the available random variables.
|Date of creation:||Dec 2001|
|Publication status:||Published in Theory and Decisions (2004), 56: 345-357|
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- David Schmeidler, 2000.
"Utility in Case-Based Decision Theory,"
00-06, Ohio State University, Department of Economics.
- Gilboa,Itzhak & Schmeidler,David, 2001.
"A Theory of Case-Based Decisions,"
Cambridge University Press, number 9780521003117, December.