ArticleEntropy (Basel, Switzerland)2018
A Decomposition Method for Global Evaluation of Shannon Entropy and Local Estimations of Algorithmic Complexity.
Article in Entropy (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
- SuperARC: a test for artificial superintelligence based on compressed modelling, recursive prediction and problem complexity.Nature communications · 2026Article
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- Task-related differences in network connectivity and dynamics in people with severe opioid use disorder compared with healthy controls.Translational psychiatry · 2026Article
- Binarized neural networks converge toward algorithmic simplicity: empirical support for the learning-as-compression hypothesis.Frontiers in computational neuroscience · 2026Article
- When prediction fails: a computational complexity view of stress.Frontiers in veterinary science · 2026Article
- Teaching Recombinable Motifs Through Simple Examples.Cognitive science · 2025Article
- Permutation Entropy and Its Niche in Hydrology: A Review.Entropy (Basel, Switzerland) · 2025Review
- Cell Fate Dynamics Reconstruction Identifies TPT1 and PTPRZ1 Feedback Loops as Master Regulators of Differentiation in Pediatric Glioblastoma-Immune Cell Networks.Interdisciplinary sciences, computational life sciences · 2025Article
- Carbon pricing drives critical transition to green growth.Nature communications · 2025Article
- A Metric for the Entropic Purpose of a System.Entropy (Basel, Switzerland) · 2025Article
- Shannon Entropy Computations in Navier-Stokes Flow Problems Using the Stochastic Finite Volume Method.Entropy (Basel, Switzerland) · 2025Article
- Key Node Identification Method Based on Multilayer Neighbor Node Gravity and Information Entropy.Entropy (Basel, Switzerland) · 2024Article
- An Additively Optimal Interpreter for Approximating Kolmogorov Prefix Complexity.Entropy (Basel, Switzerland) · 2024Article
- Building Test Batteries Based on Analyzing Random Number Generator Tests within the Framework of Algorithmic Information Theory.Entropy (Basel, Switzerland) · 2024Article
- Entropy-Based Methods for Motor Fault Detection: A Review.Entropy (Basel, Switzerland) · 2024Review
- Bias in the arrival of variation can dominate over natural selection in Richard Dawkins's biomorphs.PLoS computational biology · 2024Article
- Article
- Comprehensive computational analysis of epigenetic descriptors affecting CRISPR-Cas9 off-target activity.BMC genomics · 2022Article
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6 authors.
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Abstract
We investigate the properties of a Block Decomposition Method (BDM), which extends the power of a Coding Theorem Method (CTM) that approximates local estimations of algorithmic complexity based on Solomonoff-Levin's theory of algorithmic probability providing a closer connection to algorithmic complexity than previous attempts based on statistical regularities such as popular lossless compression schemes. The strategy behind BDM is to find small computer programs that produce the components of a larger, decomposed object. The set of short computer programs can then be artfully arranged in sequence so as to produce the original object. We show that the method provides efficient estimations of algorithmic complexity but that it performs like Shannon entropy when it loses accuracy. We estimate errors and study the behaviour of BDM for different boundary conditions, all of which are compared and assessed in detail. The measure may be adapted for use with more multi-dimensional objects than strings, objects such as arrays and tensors. To test the measure we demonstrate the power of CTM on low algorithmic-randomness objects that are assigned maximal entropy (e.g., π ) but whose numerical approximations are closer to the theoretical low algorithmic-randomness expectation. We also test the measure on larger objects including dual, isomorphic and cospectral graphs for which we know that algorithmic randomness is low. We also release implementations of the methods in most major programming languages-
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