Markov Influence Diagrams

Influence Diagrams

Evaluating Influence Diagrams

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Possibilistic Influence Diagrams

In this article we present the framework of Possibilistic Influence Diagrams (PID), which allow to model in a compact form problems of sequential decision making under uncertainty, when only ordinal data on transitions likelihood or preferences are available. The graphical part of a PID is exactly the same as that of usual influence diagrams, however the semantics differ. Transition likelihoods...

Evaluating Influence Diagrams

In this paper we will survey the history of Influence Diagrams from their origin in Decision Theory to modern AI uses. We will compare the various methods that have been used to find an optimal strategy for a given influence diagram. These methods have various advantages under different assumptions and there is a progression to the present of richer, more general solutions. We also look at an a...

Multi-objective Influence Diagrams

We describe multi-objective influence diagrams, based on a set of p objectives, where utility values are vectors in R, and are typically only partially ordered. These can still be solved by a variable elimination algorithm, leading to a set of maximal values of expected utility. If the Pareto ordering is used this set can often be prohibitively large. We consider approximate representations of ...