  We present a method for calculation of myopic value of information in
influence diagrams (Howard & Matheson, 1981) based on the strong junction tree
framework (Jensen, Jensen & Dittmer, 1994). The difference in instantiation
order in the influence diagrams is reflected in the corresponding junction
trees by the order in which the chance nodes are marginalized. This order of
marginalization can be changed by table expansion and in effect the same
junction tree with expanded tables may be used for calculating the expected
utility for scenarios with different instantiation order. We also compare our
method to the classic method of modeling different instantiation orders in the
same influence diagram.
