To make qualified decisions when extrapolating results from a survey sample with imprecise tests requires careful handling of uncertainty. Both the imprecise test and uncertainty introduced by the sampling have to be taken into account in order to act optimally. This paper formulates an influence diagram with discrete and continuous nodes to handle an example typical for animal production: a ve...

W e study a revenue management problem involving competing firms. We assume the presence of a continuum of infinitesimal firms where no individual firm has any discernable influence over the evolution of the overall market condition. Under this nonatomic-game approach, the unanimous adoption of an equilibrium pricing policy by all firms will yield a market-condition process that in turn will el...

We propose and evaluate a decision-theoretic approach for selecting tutorial actions by looking ahead to anticipate their effects on the student and other aspects of the tutorial state. The approach uses a dynamic decision network to consider the tutor's uncertain beliefs and objectives in adapting to and managing the changing tutorial state. Prototype action selection engines for diverse domai...

We discuss the use of a hybrid system utilizing Object Oriented Bayesian networks and influence diagrams for probabilistic reasoning under uncertainties in industrial process operations. The Bayesian networks are used for condition monitoring and root cause analysis of process operation. The recommended decision sequence of corrective actions and observations is obtained following the “myopic” ...

The main objectives of this note are to point out some strengths and some limitations of Kirkwood’s algebraic method for decision problems, and to propose a modification to address the limitations. The modification is based on the valuation network technique, and it enables us to better relate Kirkwood’s method to the graphical techniques of valuation networks and influence diagrams.

This paper shows the creation of the adaptive SCORM sequencing models, taking advantage of the latest developments offered by the artificial intelligence field, to provide the best choice to the student, based in learning objects, using a tutor model in self learning. The Tutor uses decision networks also called influence diagrams, to improve the development of resources and learning materials ...

The individual preference effect supplements the predominant group-level explanations for the failure of groups to solve hidden profiles. Even in the absence of dysfunctional group-level processes, group members tend to stick to their suboptimal initial decision preferences due to preference-consistent evaluation of information. However, previous experiments demonstrating this effect retained t...

The aim of this paper is to develop a strategic plan for selecting the best options for the supply of raw material to feed paper producing plants. The decision-making is examined within the framework of benefits, opportunities, costs, and risks (BOCR). A hierarchy is used to prioritize the BOCR, using the Analytic Hierarchy Process (AHP) ratings approach. A control hierarchy is then created and...

Performing sensitivity analysis for influence diagrams using the decision circuit framework is particularly convenient, since the partial derivatives with respect to every parameter are readily available [Bhattacharjya and Shachter, 2007; 2008]. In this paper we present three non-linear sensitivity analysis methods that utilize this partial derivative information and therefore do not require re...

Expressing spatial information with iconic gestures is abundant in human communication and requires to transform information about a referent into resembling gestural form. This transformation is barely understood and hard to model for expressive virtual agents as it is influenced by the visuo-spatial features of the referent, the overall discourse context or concomitant speech, and its outcome...