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Artificial Life

Spring 2015, Vol. 21, No. 2, Pages 205-224
(doi: 10.1162/ARTL_a_00157)
© 2015 Massachusetts Institute of Technology
Complexity Measurement Based on Information Theory and Kolmogorov Complexity
Article PDF (1.54 MB)
Abstract

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.