Abstract: This paper proposes a new decision making approch
based on quantitative possibilistic influence diagrams which are
extension of standard influence diagrams in the possibilistic framework.
We will in particular treat the case where several expert
opinions relative to value nodes are available. An initial expert assigns
confidence degrees to other experts and fixes a similarity threshold
that provided possibility distributions should respect. To illustrate our
approach an evaluation algorithm for these multi-source possibilistic
influence diagrams will also be proposed.
Abstract: Influence diagrams (IDs) are one of the most commonly used graphical decision models for reasoning under uncertainty. The quantification of IDs which consists in defining conditional probabilities for chance nodes and utility functions for value nodes is not always obvious. In fact, decision makers cannot always provide exact numerical values and in some cases, it is more easier for them to specify qualitative preference orders. This work proposes an adaptation of standard IDs to the qualitative framework based on possibility theory.