Cardiovascular conditions account for more medical costs than any other diagnostic category in the United States. Increasingly, economic constraints will shape policy related to health care and research. Hypertension is the most common cardiovascular condition, and despite low unit health care costs, the aggregate costs are considerable. However, the unit and aggregate costs of the complication...

In the original formulation of influence diagrams, each model contained exacly one utility node. Tatman and Shachter (1990) introduced the possibility of having super-value nodes that represent the sum or the product of their parents’ utility functions. However the algorithm they proposed for dealing with super-value nodes has two shortcomings: it requires dividing potentials when reversing arc...

This paper is concerned with the general problem of constructing decision tables and more specifically, with the identification of all possible outcomes of decisions. We introduce and propose basic influence diagrams as a simple way of describing problems of decision making under strict uncertainty. We then establish a correspondence between basic influence diagrams and symmetric generalised as...

When modeling a decision problem using the influence diagram framework, the quantitative part rests on two principal components: probabilities for representing the decision maker’s uncertainty about the domain and utilities for representing preferences. Over the last decade, several methods have been developed for learning the probabilities from a database. However, methods for learning the uti...

Influence diagrams are intuitive and concise representations of structured decision problems. When the problem is non-Markovian, an optimal strategy can be exponentially large in the size of the diagram. We can avoid the inherent intractability by constraining the size of admissible strategies, giving rise to limited memory influence diagrams. A valuable question is then how small do strategies...

This paper describes some results of research on associate systems: knowledge-based systems that flexibly and adaptively support their human users in carrying out complex, time-dependent problem-solving tasks under uncertainty. Based on principles derived from decision theory and decision analysis, a problem-solving approach is presented which can overcome many of the limitations of traditional...

We welcome this opportunity to acknowledge the significance of Judea Pearl’s contributions to uncertain reasoning and in particular to his work on causality. In the decision analysis community causality had long been “taboo” even though it provides a natural framework to communicate with decision makers and experts [Shachter and Heckerman 1986]. Ironically, while many of the concepts and method...

A multiple-output function can be represented by a binary decision diagram for characteristic function (BDD for CF). This paper presents a method to represent multiple-output incompletely specified functions using BDD for CFs. An algorithm to reduce the widths of BDD for CFs is presented. This method is useful for decomposition of incompletely specified multiple-output functions. Experimental r...

Inertial particles are finite-sized objects that are carried by flows, for example sand particles in air. In contrast to massless tracer particles, the trajectories of inertial particles can intersect in space-time. When this occurs, the inertial flow map gradient becomes singular. This has an impact on visualization concepts that require the flow map gradient to be invertible. An example are i...