What question did this study set out to answer?

The study aims to explore how regulators must incorporate internal models of the systems they control, proving this through algorithmic complexity analysis.

February 28, 2026EntropyOpen Access

The Algorithmic Regulator

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GRGiulio RuffiniBethany University

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Implication

This research analyzes algorithmic regulation, indicating the importance of internal models in systems for effective control.

Key Points

The study aims to explore how regulators must incorporate internal models of the systems they control, proving this through algorithmic complexity analysis.
Analyzed the regulator theorem under specific conditions
Modeled the world-regulator system as a self-delimiting program
Evaluated regulation as a problem of compression and algorithmic complexity
Established a correlation between algorithmic complexity reduction and effective regulation
Proved that larger complexity gaps favor higher mutual algorithmic information between world-regulator pairs
Demonstrated that low mutual information becomes exponentially unlikely as complexity gaps increase

Cite This Study

Giulio Ruffini (2026) studied this question.

synapsesocial.com/papers/69a286950a974eb0d3c01aa0 https://doi.org/10.3390/e28030257

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The Algorithmic Regulator

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Key Points

Cite This Study

The Algorithmic Regulator

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Member takes

Implication

Key Points

Cite This Study

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