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Complexity Measurement Based on Information Theory and Kolmogorov Complexity

Lookup NU author(s): Professor Natalio KrasnogorORCiD


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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.

Publication metadata

Author(s): Lui LT, Terrazas G, Zenil H, Alexander C, Krasnogor N

Publication type: Article

Publication status: Published

Journal: Artificial Life

Year: 2015

Volume: 21

Issue: 2

Pages: 205-224

Online publication date: 22/05/2015

Acceptance date: 01/01/1900

ISSN (print): 1064-5462

ISSN (electronic): 1530-9185

Publisher: Massachusetts Institute of Technology


DOI: 10.1162/ARTL_a_00157


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Funder referenceFunder name
EP/G042462/1UK EPSRC
EP/H010432/1UK EPSRC
EP/J004111/1UK EPSRC