  Distributed computation in artificial life and complex systems is often
described in terms of component operations on information: information storage,
transfer and modification. Information modification remains poorly described
however, with the popularly-understood examples of glider and particle
collisions in cellular automata being only quantitatively identified to date
using a heuristic (separable information) rather than a proper
information-theoretic measure. We outline how a recently-introduced axiomatic
framework for measuring information redundancy and synergy, called partial
information decomposition, can be applied to a perspective of distributed
computation in order to quantify component operations on information. Using
this framework, we propose a new measure of information modification that
captures the intuitive understanding of information modification events as
those involving interactions between two or more information sources. We also
consider how the local dynamics of information modification in space and time
could be measured, and suggest a new axiom that redundancy measures would need
to meet in order to make such local measurements. Finally, we evaluate the
potential for existing redundancy measures to meet this localizability axiom.
