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Expected Utility, Jeffrey's Decision Theory, and the Paradoxes

Mongin, Philippe and Baccelli, Jean (2020) Expected Utility, Jeffrey's Decision Theory, and the Paradoxes. Synthese. ISSN 1573-0964

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Abstract

In Richard Bradley's book, Decision Theory with a Human Face (2017), we have selected two themes for discussion. The first is the Bolker-Jeffrey (BJ) theory of decision, which the book uses throughout as a tool to reorganize the whole field of decision theory, and in particular to evaluate the extent to which expected utility (EU) theories may be normatively too demanding. The second theme is the redefinition strategy that can be used to defend EU theories against the Allais and Ellsberg paradoxes, a strategy that the book by and large endorses, and even develops in an original way concerning the Ellsberg paradox. We argue that the BJ theory is too specific to fulfil Bradley’s foundational project and that the redefinition strategy fails in both the Allais and Ellsberg cases. Although we share Bradley’s conclusion that EU theories do not state universal rationality requirements, we reach it not by a comparison with BJ theory, but by a comparison with the non-EU theories that the paradoxes have heuristically suggested.


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Item Type: Published Article or Volume
Creators:
CreatorsEmailORCID
Mongin, Philippemongin@greg-hec.com
Baccelli, Jeanjean.baccelli@gmail.com0000-0003-0275-0377
Keywords: Normative decision theory; Expected utility theory; Bolker-Jeffrey theory; Allais paradox; Ellsberg paradox; Bradley
Subjects: General Issues > Decision Theory
Specific Sciences > Economics
General Issues > Game Theory
Specific Sciences > Probability/Statistics
Depositing User: Jean Baccelli
Date Deposited: 16 Sep 2021 18:41
Last Modified: 16 Sep 2021 18:41
Item ID: 19568
Journal or Publication Title: Synthese
Publisher: Springer (Springer Science+Business Media B.V.)
DOI or Unique Handle: 10.1007/s11229-020-02691-3
Subjects: General Issues > Decision Theory
Specific Sciences > Economics
General Issues > Game Theory
Specific Sciences > Probability/Statistics
Date: 2020
ISSN: 1573-0964
URI: http://philsci-archive.pitt.edu/id/eprint/19568

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