Complexity measurement based on information theory and kolmogorov complexity.
Complexity measurement based on information theory and kolmogorov complexity.
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基于信息论和柯尔莫哥洛夫复杂度的复杂度测量。
DOI：
10.1162/artl_a_00157
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发表时间：
2015
期刊：
影响因子：
2.6
通讯作者：
Lui LT
中科院分区：
文献类型：
--
作者：
Lui LT
在过去的几十年里，人们提出了许多关于复杂性的定义。这些定义大多是基于香农的信息论或柯尔莫哥洛夫复杂性；这两者经常被比较，但很少有研究将两者结合起来。在本文中，我们将介绍建立在这两种理论基础上的一种新的复杂性度量。为了证明这一概念，该技术被应用于初级元胞自动机和卟啉分子自组织的模拟。
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.