Active Information Fusion

Efficient Computation of nonmyopic
ValueofInformation
A common scenario in decision making is that, given a
decision problem on hand, and a lot of information sources, what
information are deserved to be used, or used first? Valueofinformation
analysis provides a straightforward means for selecting the best next
observation to make, for determining whether it is better to gather
additional information or to act immediately. However, it requires a
consideration of the value of making all possible sequences of
observations, which is intractable in real applications. Thus people have
to make a myopic assumption: only one additional test will be performed,
even when there is an opportunity to make a large number of observations.
However, such an assumption is not reasonable in a lot of applications.
Thus, we propose an approximate algorithm to compute nonmyopic
valueofinformation efficiently. With this algorithm, the
valueofinformation can be computed efficiently for any group of
information sources, thus makes it possible for people to choose best
information sources for decisionmaking. The figure
below illustrates the steps of the proposed algorithm. More
detail can be found at Here.
