Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/159127
Authors: 
Giusti, Giuliano
Zagonari, Fabio
Year of Publication: 
1997
Series/Report no.: 
Quaderni - Working Paper DSE 284
Abstract: 
This paper identifies in a feed-forward neural network the mathematical algorithm which can catch the learning process highlighted by econometric works that makes people assess the satisfaction arising in each single contingency so that they are better depicted in their decision making by an Expected Utility rather than by a Regret Model. Evidence from experimental economics are also accounted for, since the network does not manage to extrapolate the former from the latter model when probabilities are extreme.
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by-nc/3.0/
Document Type: 
Working Paper

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