  The logical basis for information theory is the newly developed logic of
partitions that is dual to the usual Boolean logic of subsets. The key concept
is a "distinction" of a partition, an ordered pair of elements in distinct
blocks of the partition. The logical concept of entropy based on partition
logic is the normalized counting measure of the set of distinctions of a
partition on a finite set--just as the usual logical notion of probability
based on the Boolean logic of subsets is the normalized counting measure of the
subsets (events). Thus logical entropy is a measure on the set of ordered
pairs, and all the compound notions of entropy (join entropy, conditional
entropy, and mutual information) arise in the usual way from the measure (e.g.,
the inclusion-exclusion principle)--just like the corresponding notions of
probability. The usual Shannon entropy of a partition is developed by replacing
the normalized count of distinctions (dits) by the average number of binary
partitions (bits) necessary to make all the distinctions of the partition.
