Boundary Pressure as a Universal Driver Across Domains

This paper proposes that boundary-induced indeterminacy generates a universal form of structural pressure ($F_B$) that drives system evolution across disparate domains. Within the Theory of Non-Derivable Admissibility (TNA) framework, $F_B$ emerges whenever a system encounters its limits of validity, manifesting as singularities in physics, out-of-distribution (OOD) failures in machine learning, and paradoxes in cognition. We argue that these phenomena are not errors or terminal points, but rather structural signals and generative forces that trigger subsequent adaptation. By defining a unified structural law where boundary indeterminacy leads to domain expansion ($\Omega \rightarrow \Omega^+$), this work establishes expansion under constraint as a domain-independent principle. Ultimately, we show that systems evolve indefinitely by confronting their inherent limits, transforming structural failure into the primary driver of evolution.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-15
DOI
https://doi.org/10.5281/zenodo.19597408
Primary Topic
Evolutionary Algorithms and Applications
Type
article
Field-Weighted Citation Impact
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article

Boundary Pressure as a Universal Driver Across Domains

Claudio Bresciano
Zenodo (CERN European Organization for Nuclear Research)
Evolutionary Algorithms and Applications
article

Boundary Pressure as a Universal Driver Across Domains

Claudio Bresciano
article en

Abstract

This paper proposes that boundary-induced indeterminacy generates a universal form of structural pressure ($F_B$) that drives system evolution across disparate domains. Within the Theory of Non-Derivable Admissibility (TNA) framework, $F_B$ emerges whenever a system encounters its limits of validity, manifesting as singularities in physics, out-of-distribution (OOD) failures in machine learning, and paradoxes in cognition. We argue that these phenomena are not errors or terminal points, but rather structural signals and generative forces that trigger subsequent adaptation. By defining a unified structural law where boundary indeterminacy leads to domain expansion ($\Omega \rightarrow \Omega^+$), this work establishes expansion under constraint as a domain-independent principle. Ultimately, we show that systems evolve indefinitely by confronting their inherent limits, transforming structural failure into the primary driver of evolution.

Zenodo (CERN European Organization for Nuclear Research)
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Evolutionary Algorithms and Applications
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