Algorithmic Specified Complexity in the Game of Life

Algorithmic specified complexity (ASC) measures the degree to which an object is meaningful. Neither fundamental Shannon nor Kolmogorov information models are equipped to do so. ASC uses performance context in an information theoretic framework to measure the degree of specified complexity in bits....

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Bibliographic Details
Published in:IEEE transactions on systems, man, and cybernetics. Systems Vol. 45; no. 4; pp. 584 - 594
Main Authors: Ewert, Winston, Dembski, William, Marks, Robert J.
Format: Journal Article
Language:English
Published: IEEE 01.04.2015
Subjects:
Algorithmic specified complexity
cellular automata
Complexity theory
Context
Conway's Game of Life
Encoding
Equations
Games
Kolmogorov information
Kolmogorov-Chaitin-Solomonoff information
Mathematical model
Shannon information
specified complexity
Conway’s Game of Life
Shannon information
Kolmogorov-Chaitin-Solomonoff information
Kolmogorov information
Algorithmic specified complexity
cellular automata
specified complexity
ISSN:2168-2216, 2168-2232
Online Access:Get full text
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Summary:Algorithmic specified complexity (ASC) measures the degree to which an object is meaningful. Neither fundamental Shannon nor Kolmogorov information models are equipped to do so. ASC uses performance context in an information theoretic framework to measure the degree of specified complexity in bits. To illustrate, we apply ASC to Conway's Game of Life to differentiate patterns designed by programmers from those originating by chance. A variety of machines created by Game of Life hobbyists, as expected, exhibit high ASC thereby corroborating ASC's efficacy.
ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2014.2331917