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Two-dimensional Kolmogorov complexity and an empirical validation of the Coding theorem method by compressibility

Opened Access Two-dimensional Kolmogorov complexity and an empirical validation of the Coding theorem method by compressibility

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Autor: Zenil, Hector
Soler Toscano, Fernando
Delahaye, Jean-Paul
Gauvrit, Nicolas
Departamento: Universidad de Sevilla. Departamento de Filosofía y Lógica y Filosofía de la Ciencia
Fecha: 2015
Publicado en: PeerJ Computer Sciense, 1:e23, 1-31.
Tipo de documento: Artículo
Resumen: We propose a measure based upon the fundamental theoretical concept in algorithmic information theory that provides a natural approach to the problem of evaluating n-dimensional complexity by using an n-dimensional deterministic Turing machine. The technique is interesting because it provides a natural algorithmic process for symmetry breaking generating complex n-dimensional structures from perfectly symmetric and fully deterministic computational rules producing a distribution of patterns as described by algorithmic probability. Algorithmic probability also elegantly connects the frequency of occurrence of a pattern with its algorithmic complexity, hence effectively providing estimations to the complexity of the generated patterns. Experiments to validate estimations of algorithmic complexity based on these concepts are presented, showing that the measure is stable in the face of some changes in computational formalism and that results are in agreement with the results obtained usin...
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Cita: Zenil, H., Soler Toscano, F., Delahaye, J. y Gauvrit, N. (2015). Two-dimensional Kolmogorov complexity and an empirical validation of the Coding theorem method by compressibility. PeerJ Computer Sciense, 1:e23, 1-31.
Tamaño: 2.919Mb
Formato: PDF

URI: http://hdl.handle.net/11441/64223

DOI: 10.7717/peerj-cs.23

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