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 |