Vector Storm Theory: Instability Dynamics in Multi-Agent Systems

Vector Storm Theory provides an effective dynamical framework for diagnosing, predicting, and comparing instability regimes in emerging multi-agent AI ecosystems. Empirical grounding constraints and measurement environment classification are specified in the companion measurement framework, Critical Phenomena in Multi-Agent Systems (v2.0).

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-23
DOI
https://doi.org/10.5281/zenodo.18742838
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

Vector Storm Theory: Instability Dynamics in Multi-Agent Systems

Bin Seol
Zenodo (CERN European Organization for Nuclear Research)
Neural Networks and Reservoir Computing
article

Vector Storm Theory: Instability Dynamics in Multi-Agent Systems

Bin Seol
article en

Abstract

Vector Storm Theory provides an effective dynamical framework for diagnosing, predicting, and comparing instability regimes in emerging multi-agent AI ecosystems. Empirical grounding constraints and measurement environment classification are specified in the companion measurement framework, Critical Phenomena in Multi-Agent Systems (v2.0).

Zenodo (CERN European Organization for Nuclear Research)
Life in Land
Openalex Percentile: Top 50%
Neural Networks and Reservoir Computing
DOIOpen Access PDFOpenAlex
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