title: Partial information decomposition as a spatiotemporal filter.
abstract: Understanding the mechanisms of distributed computation in cellular automata requires techniques for characterizing the emergent structures that underlie information processing in such systems. Recently, techniques from information theory have been brought to bear on this problem. Building on this work, we utilize the new technique of partial information decomposition to show that previous information-theoretic measures can confound distinct sources of information. We then propose a new set of filters and demonstrate that they more cleanly separate out the background domains, particles, and collisions that are typically associated with information storage, transfer, and modification in cellular automata.
authors.affiliation: Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana 47406, USA.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Flecker
authors.forename: Wesley
authors.initials: W
authors.lastname: Alford
authors.forename: John M
authors.initials: JM
authors.lastname: Beggs
authors.forename: Paul L
authors.initials: PL
authors.lastname: Williams
authors.forename: Randall D
authors.initials: RD
authors.lastname: Beer
mesh_terms: D019277:Entropy; D007257:Information Theory; D008962:Models, Theoretical; D013997:Time Factors