Expected Information as Expected Utility

Abstract

The normative procedure for the desing of an experiment is to select a utility function, assess the probabilities, and to choose that design of maximum expected utility. One difficulty with this view is that a scientist typically dose not have, nor can be normally expected to have, a clear idea of the utility of his results. An alternative is to design an experiment to maximize the expected information to be gained from it. In this paper we show that the latter view is a special case of the former with an appropriate chose of the decision space and a resonable constraint on the utility function. In particular, the Shannon concept of information is seen to play a more important role in experimental design that was hitherto thought possible.