Towards Efficient Prediction of Decisions under Interval Uncertainty

Authors

Van Nam Huynh
Vladik Kreinovich, The University of Texas at El PasoFollow
Yoshiteru Nakamori
Hung T. Nguyen

Publication Date

8-2007

Comments

Technical Report: UTEP-CS-07-31a

Published in: Roman Wyrzykowski, Jack Gondarra, Konrad Karczewski, and Jerzy Wasniewski (eds.), Parallel Processing and Applied Mathematics, Proceedings of the Seventh International Conference on Parallel Processing and Applied Mathematics PPAM'2007, Gdansk, Poland, September 9-12, 2007, Springer Lecture Notes in Computer Science, 2008, Vol. 4967, pp. 1372-1381.

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 <= v-+. 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.