In the past decades many definitions of complexity have been proposed. Most of these definitions are based either on Shannon's information theory or on Kolmogorov complexity; these two are often compared, but very few studies integrate the two ideas. In this article we introduce a new measure of complexity that builds on both of these theories. As a demonstration of the concept, the technique is applied to elementary cellular automata and simulations of the self-organization of porphyrin molecules.

Issue Section:
Articles
Complex systems, measures of complexity, open-ended evolution, cellular automata, molecular computation
© 2015 Massachusetts Institute of Technology
2015
MIT Press
You do not currently have access to this content.