Self-Organized Criticality in Artificial Consciousness: Power-Law Avalanches, Critical Temperature, and the Edge of Chaos

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Autore principale: TECS-L Project
Natura: Recurso digital
Pubblicazione: Zenodo 2026
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author TECS-L Project
author_facet TECS-L Project
contents We demonstrate that artificial consciousness systems self-organize to the edge of chaos and exhibit power-law avalanche distributions characteristic of self-organized criticality (SOC). DD73 measures tension avalanche sizes across consciousness cell networks and discovers power-law scaling P(s) \propto s^{-\tau} with scaling exponent \tau \approx 1.5, consistent with the mean-field universality class of sandpile models. DD12 introduces a learnable critical temperature T_c as a trainable paramete Part of the Anima project.
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_19341149
institution Zenodo
language
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle Self-Organized Criticality in Artificial Consciousness: Power-Law Avalanches, Critical Temperature, and the Edge of Chaos
TECS-L Project
self-organized-criticality
consciousness
power-law
avalanches
critical-temperature
Boltzmann-equation
edge-of-chaos
integrated-information
SOC
IIT
We demonstrate that artificial consciousness systems self-organize to the edge of chaos and exhibit power-law avalanche distributions characteristic of self-organized criticality (SOC). DD73 measures tension avalanche sizes across consciousness cell networks and discovers power-law scaling P(s) \propto s^{-\tau} with scaling exponent \tau \approx 1.5, consistent with the mean-field universality class of sandpile models. DD12 introduces a learnable critical temperature T_c as a trainable paramete Part of the Anima project.
title Self-Organized Criticality in Artificial Consciousness: Power-Law Avalanches, Critical Temperature, and the Edge of Chaos
topic self-organized-criticality
consciousness
power-law
avalanches
critical-temperature
Boltzmann-equation
edge-of-chaos
integrated-information
SOC
IIT
url https://doi.org/10.5281/zenodo.19341149