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

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.

• Type: Conference
• Year: 2005
• Where: ISIPTA
• Authors: Lev V. Utkin, Thomas Augustin
• Keywords: Arbitrary Ambiguity Attitudes, ISIPTA 2005, Mathematics, Paper Discusses Decision, Partial Prior Information