What can (partition) logic contribute to information theory?

Basically this paper shows how the notion of logical entropy arises out of the logic of partitions dual to ordinary logic of subsets (‘propositional’ logic) and then turns to showing how logical entropy compares favorably to the standard notion of Shannon entropy. Thus the last part of the paper is essentially a critique of Shannon entropy.

Information as distinctions

This paper is sub-titled “New Foundations for Information Theory” since it is based on the logical notion of entropy from the logic of partitions. The basic logical idea is that of “distinctions.” Logical entropy is normalized counting measure of the set of distinctions of a partition, and Shannon entropy is the number of binary partitions needed, on average, to make the same distinctions of the partition.

From Partition Logic to Information Theory

A new logic of partitions has been developed that is dual to ordinary logic when the latter is interpreted as the logic of subsets rather than the logic of propositions. For a finite universe, the logic of subsets gave rise to finite probability theory by assigning to each subset its relative cardinality as a Laplacian probability. The analogous development for the dual logic of partitions gives rise to a notion of logical entropy that is related in a precise manner to Claude Shannon’s entropy.