I'm interested in methods/heuristics for selecting a group of test variables that have a large/largest value of information. Most approaches are myopic (i.e., select the variable with maximal VOI, test its value, select the next one, etc.). I found only two relevant references: Heckerman et al. 1993 discuss approximate non-myopic VOI computation, and Madigan and Russell 1995 discuss test selection strategies. Both say that it is a key capability of an expect system, but surprisintly I could not find any work beyond this. In particular, I'm happy with the Heckerman et al. model in which there is a single binary decision and a single binary chance node affecting the value function.
Can anyone recommend additional useful references? Thanks, Ronen
