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基于信息论和柯尔莫哥洛夫复杂度的复杂性度量。

Complexity measurement based on information theory and kolmogorov complexity.

作者信息

Lui Leong Ting, Terrazas Germán, Zenil Hector, Alexander Cameron, Krasnogor Natalio

机构信息

University of Nottingham.

University of Sheffield.

出版信息

Artif Life. 2015 Spring;21(2):205-24. doi: 10.1162/ARTL_a_00157. Epub 2015 Jan 26.

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.

摘要

在过去几十年里,人们提出了许多关于复杂性的定义。这些定义大多基于香农信息论或柯尔莫哥洛夫复杂性;这两者经常被比较,但很少有研究将这两种思想结合起来。在本文中,我们引入了一种基于这两种理论的新的复杂性度量。作为该概念的一个例证,该技术被应用于基本细胞自动机和卟啉分子自组织的模拟。

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