  We illustrate an application of Algorithmic Information Dynamics to Cellular
Automata (CA) demonstrating how this digital calculus is able to quantify
change in discrete dynamical systems. We demonstrate the sensitivity of the
Block Decomposition Method on 1D and 2D CA, including Conway's Game of Life,
against measures of statistical nature such as compression (LZW) and Shannon
Entropy in two different contexts (1) perturbation analysis and (2)
dynamic-state colliding CA. The approach is interesting because it analyses a
quintessential object native to software space (CA) in software space itself by
using algorithmic information dynamics through a model-driven universal search
instead of a traditional statistical approach e.g. LZW compression or Shannon
entropy. The colliding example of two state-independent (if not three as one is
regulating the collision itself) discrete dynamical systems offers a potential
proof of concept for the development of a multivariate version of the AID
calculus.
