Optimizing the Hurwicz criterion in decision trees with imprecise probabilities

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Abstract

This paper is devoted to sequential decision problems with imprecise probabilities. We study the problem of determining an optimal strategy according to the Hurwicz criterion in decision trees. More precisely, we investigate this problem from the computational viewpoint. When the decision tree is separable (to be defined in the paper), we provide an operational approach to compute an optimal strategy, based on a bicriteria dynamic programming procedure. The results of numerical tests are presented. When the decision tree is non-separable, we prove the NP-hardness of the problem. © 2009 Springer-Verlag Berlin Heidelberg.

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APA

Jeantet, G., & Spanjaard, O. (2009). Optimizing the Hurwicz criterion in decision trees with imprecise probabilities. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5783 LNAI, pp. 340–352). https://doi.org/10.1007/978-3-642-04428-1_30

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