Since their introduction in the mid 1970s, influence diagrams have become a de facto
standard for representing Bayesian decision problems. The need to represent complex …

Bayesian networks (BNs) and influence diagrams (IDs) are probabilistic graphical models
that are widely used for building diagnosis-and decision-support expert systems …

Influence diagrams have become a popular tool for representing and solving complex
decision-making problems under uncertainty. In this paper, we focus on the task of building …

Background. Neonatal jaundice is treated daily at all hospitals. However, the routine,
urgency, and case load of most doctors stop them from carefully analyzing all the factors that …

An Indexed Bibliography of Genetic Algorithms in Economics Page 1 An Indexed Bibliography
of Genetic Algorithms in Economics compiled by Jarmo T. Alander Department of Electrical …

Influence diagrams (IDs) are a powerful tool for representing and solving decision problems
under uncertainty. The objective of evaluating an ID is to compute the expected utility and an …

An Indexed Bibliography of Genetic Algorithms in Operations Research Page 1 An Indexed
Bibliography of Genetic Algorithms in Operations Research compiled by Jarmo T. Alander …

When solving clinical decision-making problems with modern graphical decision-theoretic
models such as influence diagrams, we obtain decision tables with optimal decision …

When solving decision-making problems with modern graphical models like influence
diagrams, we obtain the decision tables with optimal decision alternatives. For real-life …

This paper presents a generalized theory for capturing and manipulating classification
information. We define decision algebra which models decision-based classifiers as higher …