Measuring the Complexity of Continuous Distributions
Adaptation and Self-Organizing Systems
2016-04-01 v1 Statistical Mechanics
Computational Complexity
Abstract
We extend previously proposed measures of complexity, emergence, and self-organization to continuous distributions using differential entropy. This allows us to calculate the complexity of phenomena for which distributions are known. We find that a broad range of common parameters found in Gaussian and scale-free distributions present high complexity values. We also explore the relationship between our measure of complexity and information adaptation.
Cite
@article{arxiv.1511.00529,
title = {Measuring the Complexity of Continuous Distributions},
author = {Guillermo Santamaría-Bonfil and Nelson Fernández and Carlos Gershenson},
journal= {arXiv preprint arXiv:1511.00529},
year = {2016}
}
Comments
21 pages, 5 Tables, 4 Figures