FOURTH INTERNATIONAL SYMPOSIUM ON
IMPRECISE PROBABILITIES AND THEIR APPLICATIONS
Carnegie Mellon University
Pittsburgh, PA, USA
July 20-23 2005

ISIPTA'05 ELECTRONIC PROCEEDINGS

Lev Utkin, Thomas Augustin

Powerful algorithms for decision making under partial prior information and general ambiguity attitudes

Abstract

This paper discusses decision making in the practically important situation where only partial prior information on the stochastic behavior of the states of nature expressed by imprecise probabilities (interval probability) is available. For this situation, in literature several optimality criteria have been suggested and investigated theoretically. Practical computation of optimal solutions, however, is far from being straightforward. The paper develops powerful algorithms for determining optimal actions under arbitrary ambiguity attitudes and the criterion of E-admissibility. The algorithms are based on linear programming and can be implemented by standard software.

Keywords. ambiguity attitudes, Choquet expected utility, decision making, E-admissibility, imprecise probabilities, interval probability, interval statistical models, linear programming, MaxEMin criterion, maximality, maxmin expected utility model, minimality, partial prior information, structure dominance

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Authors addresses:

Lev Utkin
Department of Computer Science,
St. Petersburg Forest Technical Academy
Institutski per. 5,
St. Petersburg, 194021

Thomas Augustin
Department of Statistics
University of Munich
Ludwigstr. 33
D-80539 Munich
Germany

E-mail addresses:

Lev Utkin lvu@utkin.usr.etu.spb.ru
Thomas Augustin thomas@stat.uni-muenchen.de


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