[UAI] Non myopic Test selection/value of information

From: Ronen Brafman (brafman@cs.bgu.ac.il)
Date: Mon May 27 2002 - 17:20:03 PDT

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    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

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