id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_z6a2e7o6xneifhhzpx4u5zutgi	Hector Zenil	Two-dimensional Kolmogorov complexity and an empirical validation of the Coding theorem method by compressibility	2015	31	.pdf	application/pdf	11780	1258	45	The technique is interesting because it provides a natural algorithmic process for symmetry breaking generating complex n-dimensional structures frequency of the set of 2-dimensional Turing machines to classify the algorithmic results from the Coding theorem method to approximate the Kolmogorov complexity of Figure 2 The top 36 objects in D(4,2)2D preceded by their Km,2D values, sorted by higher to lower frequency and therefore from smaller to larger Kolmogorov complexity after application of the Coding lossless compression method as approximation techniques to Kolmogorov complexity. length (files with more complex (random) strings are expected to be less compressible Figure 7 Top: Distribution of complexity values for different string lengths (l). and smallest to largest compression lengths using the Deflate algorithm as a method to approximate Kolmogorov complexity (Zenil, 2010). Two-dimensional Kolmogorov complexity and an empirical validation of the Coding theorem method by compressibility Two-dimensional Kolmogorov complexity and an empirical validation of the Coding theorem method by compressibility	./cache/work_z6a2e7o6xneifhhzpx4u5zutgi.pdf	./txt/work_z6a2e7o6xneifhhzpx4u5zutgi.txt