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Entropy 2008, 10(1), 6-14; doi:10.3390/entropy-e10010006
Article

An Algorithmic Complexity Interpretation of Lin's Third Law of Information Theory

Received: 28 February 2008; in revised form: 16 March 2008 / Accepted: 19 March 2008 / Published: 20 March 2008
(This article belongs to the Special Issue Symmetry and Entropy)
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Abstract: Instead of static entropy we assert that the Kolmogorov complexity of a static structure such as a solid is the proper measure of disorder (or chaoticity). A static structure in a surrounding perfectly-random universe acts as an interfering entity which introduces local disruption in randomness. This is modeled by a selection rule R which selects a subsequence of the random input sequence that hits the structure. Through the inequality that relates stochasticity and chaoticity of random binary sequences we maintain that Lin’s notion of stability corresponds to the stability of the frequency of 1s in the selected subsequence. This explains why more complex static structures are less stable. Lin’s third law is represented as the inevitable change that static structure undergo towards conforming to the universe’s perfect randomness.
Keywords: Entropy; Randomness; Information theory; Algorithmic complexity; Binary sequences Entropy; Randomness; Information theory; Algorithmic complexity; Binary sequences
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Ratsaby, J. An Algorithmic Complexity Interpretation of Lin's Third Law of Information Theory. Entropy 2008, 10, 6-14.

AMA Style

Ratsaby J. An Algorithmic Complexity Interpretation of Lin's Third Law of Information Theory. Entropy. 2008; 10(1):6-14.

Chicago/Turabian Style

Ratsaby, Joel. 2008. "An Algorithmic Complexity Interpretation of Lin's Third Law of Information Theory." Entropy 10, no. 1: 6-14.


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