This paper describes a new algorithm to solve the decision making problem in Influence Diagrams based on algorithms for credal networks. Decision nodes are associated to imprecise...
Recent research has found that diagnostic performance with Bayesian belief networks is often surprisingly insensitive to imprecision in the numerical probabilities. For example, t...
Max Henrion, Malcolm Pradhan, Brendan Del Favero, ...
Bayesian advocates of expected utility maximization use sets of probability distributions to represent very different ideas. Strict Bayesians insist that probability judgment is n...
For cancers with more than one risk factor, the sum of probabilistic estimates of the number of cancers attributable to each individual factor may exceed the total number of cases...
Minh Ha-Duong, Elizabeth Casman, M. Granger Morgan
For many problems there is only suf£cient prior information for a Bayesian decision maker to identify a class of possible prior distributions. In such cases it is of interest to ...