## Influence Diagram

An influence diagram is a Bbn extended with decision facilities (decision nodes and utility nodes).

An influence diagram cannot contain continuous chance nodes.

An influence diagram should be constructed so that one can see exactly which variables (represented by discrete chance nodes) are known at the point of deciding for each decision node. If the state of a chance node will be known at the time of making a decision, this will (probably) have an impact on what the decision maker should do. Thus, one must add a link from the chance node to the decision node. If the state of a chance node will be known before some given decision, and this chance node has impact on another chance node which is also known before the decision, only the last chance node needs to have a link to the decision node. That is, there only needs to be a directed path from a chance node to a decision node if the chance node is known before the decision is made.

In an influence diagram, there must also be an unambiguous order among the decision nodes. That is, there can be only one sequence in which the decisions are made. In the same way as when defining that a chance node will be known before a decision is made, we add links to show which decisions have already been made when a specific decision is made. Again there only need to be a directed path from one decision node to the next one in the decision sequence.

If the influence diagram is not constructed correctly according to the rules stated above, the calculated expected utilities will (of course) not be correct.

When propagating, you can follow the expected utility of choosing each decision in the next decision node in the decision sequence either in the node list pane or by opening a monitor window for the decision node. The utilities shown in a decision node further down in the decision sequence should not be considered before all previous decisions have been made. This simply makes no sence.

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