A package for measuring emergence, self-organization, and complexity based on Shannon entropy

Guillermo Santamaría-Bonfil; Carlos Gershenson; Nelson Fernández

doi:10.3389/frobt.2017.00010

A package for measuring emergence, self-organization, and complexity based on Shannon entropy

Guillermo Santamaría-Bonfil
, Carlos Gershenson
, Nelson Fernández

School of Sys Sci Ind Engr

Binghamton University

Gerencia de Tecnologías de la Información
Universidad de Pamplona

Research output: Contribution to journal › Article › peer-review

16 Scopus citations

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.

Original language	English
Article number	10
Journal	Frontiers in Robotics and AI
Volume	4
Issue number	MAR
DOIs	https://doi.org/10.3389/frobt.2017.00010
State	Published - Mar 1 2017

Keywords

Code:Octave/Matlab
Complexity
Emergence
Machine learning datasets
Self-organization

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10.3389/frobt.2017.00010

Cite this

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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.",

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AU - Santamaría-Bonfil, Guillermo

AU - Gershenson, Carlos

AU - Fernández, Nelson

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N2 - 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.

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KW - Complexity

KW - Emergence

KW - Machine learning datasets

KW - Self-organization

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DO - 10.3389/frobt.2017.00010

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A package for measuring emergence, self-organization, and complexity based on Shannon entropy

Abstract

Keywords

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