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Proceedings Paper

Quantifying self-organization in cyclic cellular automata
Author(s): Cosma Rohilla Shalizi; Kristina Lisa Shalizi
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Paper Abstract

Cyclic cellular automata (CCA) are models of excitable media. Started from random initial conditions, they produce several different kinds of spatial structure, depending on their control parameters. We introduce new tools from information theory that let us calculate the dynamical information content of spatial random processes. This complexity measure allows us to quantitatively determine the rate of self-organization of these cellular automata, and establish the relationship between parameter values and self-organization in CCA. The method is very general and can easily be applied to other cellular automata or even digitized experimental data.

Paper Details

Date Published: 7 May 2003
PDF: 10 pages
Proc. SPIE 5114, Noise in Complex Systems and Stochastic Dynamics, (7 May 2003); doi: 10.1117/12.485805
Show Author Affiliations
Cosma Rohilla Shalizi, Univ. of Michigan (United States)
Kristina Lisa Shalizi, Univ. of Michigan (United States)

Published in SPIE Proceedings Vol. 5114:
Noise in Complex Systems and Stochastic Dynamics
Lutz Schimansky-Geier; Derek Abbott; Alexander Neiman; Christian Van den Broeck, Editor(s)

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