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Estimating Information Amount Under Interval Uncertainty: Algorithmic Solvability And Computational Complexity, Gang Xiang, Olga Kosheleva, George J. Klir

Departmental Technical Reports (CS)

In most real-life situations, we have uncertainty: we do not know the exact state of the world, there are several (n) different states which are consistent with our knowledge. In such situations, it is desirable to gauge how much information we need to gain to determine the actual state of the world. A natural measure of this amount of information is the average number of "yes"-"no" questions that we need to ask to find the exact state. When we know the probabilities p1,...,pn of different states, then, as Shannon has shown, this number of questions can be determined as S=-p1 …