Towards efficient prediction of decisions under interval uncertainty

Authors:
Van Nam Huynh;Vladik Kreinovich;Yoshiteru Nakamori;Hung T. Nguyen
Affiliations:
Japan Advanced Institute of Science and Technology, Tatsunokuchi, Ishikawa, Japan;University of Texas at El Paso, El Paso, TX;Japan Advanced Institute of Science and Technology, Tatsunokuchi, Ishikawa, Japan;New Mexico State University, Las Cruces, NM
Venue:
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Year:
2007

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Abstract

In many practical situations, users select between n alternatives a1,..., an, and the only information that we have about the utilities vi of these alternatives are bounds vi ≤ vi ≤ vi. In such situations, it is reasonable to assume that the values vi are independent and uniformly distributed on the corresponding intervals [vi, vi]. Under this assumption, we would like to estimate, for each i, the probability pi that the alternative ai will be selected. In this paper, we provide efficient algorithms for computing these probabilities.