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Cited by 12Computability, Logic, AI AlgorithmsComplex Systems and DynamicsPhilosophy of Biology and Scientific Explanation

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Generalized Active Information: Extensions to Unbounded Domains

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Marks, Robert, Díaz-Pachón, Daniel Andrés·2020·BIO-Complexity
DOI 10.5048/bio-c.2020.3
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Abstract

In the last three decades, several measures of complexity have been proposed. Up to this point, most of such measures have only been developed for finite spaces. In these scenarios the baseline distribution is uniform. This makes sense because, among other things, the uniform distribution is the measure of maximum entropy over the relevant space. Active information traditionally assumes a finite interval universe of discourse but can be extended to other cases where maximum entropy is defined. Illustrating this is the purpose of this paper. Disequilibrium from maximum entropy, measured as active information, can be evaluated from baselines with unbounded support.

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Metadata

Authors
Marks, R., & Díaz-Pachón, D. A.
Venue
BIO-Complexity
Publisher
Biologic Institute
Published
2020-03-19
Volume
2020
Issue
3
ISSN
2151-7444 (ISSN-L)
DOI
10.5048/bio-c.2020.3
OpenAlex
W3020915226
Cited by
12
References
0
Citations by year
2026: 1 · 2024: 1 · 2023: 2 · 2022: 4 · 2021: 1 · 2020: 3
FWCI
1.24
Type
journal article
Language
en
Open access
Locations
  • BIO-Complexity (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Topics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computability, Logic, AI Algorithms
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Systems and Dynamics
  • Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy of Biology and Scientific Explanation
Keywords
active information, complexity measures, maximum entropy, unbounded domains, baseline distribution, disequilibrium

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