Name
Title | ||
|---|---|---|
A Package for Measuring Emergence, Self-organization, and Complexity Based on Shannon Entropy. |
Abstract | ||
|---|---|---|
We present a set of Matlab/Octave functions to compute measures of emergence, self-organization, and complexity applied to discrete and continuous data. These measures are based on Shannon's information and differential entropy. Examples from different datasets and probability distributions are provided to show how to use our proposed code. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.3389/frobt.2017.00010 | FRONTIERS IN ROBOTICS AND AI |
Keywords | Field | DocType |
emergence,self-organization,complexity,machine learning datasets,code:Octave/Matlab | Octave,MATLAB,Computer science,Self-organization,Theoretical computer science,Probability distribution,Artificial intelligence,Differential entropy,Entropy (information theory),Machine learning | Journal |
Volume | ISSN | Citations |
4.0 | 2296-9144 | 1 |
PageRank | References | Authors |
0.35 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guillermo Santamaría Bonfil | 1 | 6 | 1.50 |
| Carlos Gershenson | 2 | 392 | 42.34 |
| Nelson Fernandez | 3 | 2 | 1.06 |