  A novel, information-based classification of elementary cellular automata is
proposed that circumvents the problems associated with isolating whether
complexity is in fact intrinsic to a dynamical rule, or if it arises merely as
a product of a complex initial state. Transfer entropy variations processed by
the system split the 256 elementary rules into three information classes, based
on sensitivity to initial conditions. These classes form a hierarchy such that
coarse-graining transitions observed among elementary cellular automata rules
predominately occur within each information- based class, or much more rarely,
down the hierarchy.
