Abstract
This paper reviews algorithms for local computation with imprecise probabilities. These algorithms try to solve problems of inference (calculation of conditional or unconditional probabilities) in cases in which there are a large number of variables. There are two main types in the literature depending on the nature of assumed independence relationships in each case. In both of them the global knowledge is composed of several pieces of information. The objective is to carry out a sound global computation bu using mainly the initial local representation.
Keywords. Propagation algorithms, Valuation Based Systems, Imprecise Probabilities
The paper is available in the following formats:
Authors addresses:Dpto. Ciencias de la Computacion
E-mail addresses:
| Andres Cano | acu@decsai.ugr.es |
| Serafin Moral | smc@decsai.ugr.es |
Related Web Sites
Uncertainty Treatment in Artificial Intelligence (research group)