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Eichberger, Jürgen
Guerdjikova, Ani
Year of Publication: 
Series/Report no.: 
Discussion Paper Series, University of Heidelberg, Department of Economics 470
In this paper, we consider a decision-maker who tries to learn the distribution of outcomes from previously observed cases. For each observed sequence of cases the decision-maker predicts a set of priors expressing his beliefs about the underlying probability distribution. We impose a version of the concatenation axiom introduced in BILLOT, GILBOA, SAMET AND SCHMEIDLER (2005) which insures that the sets of priors can be represented as a weighted sum of the observed frequencies of cases. The weights are the uniquely determined similarities between the observed cases and the case under investigation.
Document Type: 
Working Paper

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