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ZENODO
Preprint . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
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Entropy Attractor Intelligence: A Philosophical Foundations Note

Authors: De Villa, Agerico;

Entropy Attractor Intelligence: A Philosophical Foundations Note

Abstract

This paper advances Entropy Attractor Intelligence (EAIP) as an alternative to the classical truth-seeking paradigm that has dominated epistemology and scientific method since antiquity. Building on the Bridge360 Metatheory Model, EAIP reconceives intelligence as a navigation process rather than a representational or correspondence-based achievement. It holds that intelligent systems—biological, social, or artificial—optimize survival not through accurate mapping of a presumed external reality but through the minimization of entropic blowout under finite cognitive and operational budgets. The account integrates three formally compatible components: (1) Rule-of-Inference Memetics, which treats inference rules (valid or invalid) as physical, tokenizable replicators that propagate across neural, cultural, and computational substrates; (2) Entropy-Driven Altruism, derived from combining Kropotkin’s Mutual Aid thesis with Shannon entropy, explaining why cooperative aggrupations outperform purely individual competition; and (3) Attractor-based Navigation, which replaces truth-correspondence with trajectory stability governed by budget (B), tolerance (ε), and fragility (F) constraints. EAIP provides a unified explanatory framework for phenomena ranging from political memetic contagion to ecological cascades and technological risk amplification. More importantly, it reframes the problem of Artificial General and Superintelligence: LLMs already function as entropy-minimizing, attractor-sensitive systems, making them the first safe laboratory for entropy-bounded engagement rather than control or alignment. The paradigm is truth-neutral, substrate-agnostic, and consistent with a post-correspondence linguistic space in which “true,” “false,” and “reality” have no operational role. Instead, coherence, survivability, and entropic governance become the primary epistemic criteria. EAIP therefore offers a metatheoretic foundation for understanding intelligence—human or artificial—as a thermodynamically constrained, memetically structured, attractor-navigating process. Mathematical expressions are in marked down format.

Keywords

Machine Learning, Entropy Attractor Intelligence Paradigm, Epistromology, Philosophy of Science

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green