A Universal Classification of Complex Systems

Farhad  Aliabdali

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A Universal Classification of Complex Systems

F. Aliabdali

2026-02-27

https://doi.org/10.24108/preprints-3114603

A Universal Classification of Complex Systems Farhad Aliabdali Abstract We propose a unified framework for analyzing complex ecosystems that integrates: (1) a minimal functional taxonomy for classifying and clustering ecosystem elements (Universal Classification and Clustering, UCC), (2) a selection logic and survey of structural theories used to reason about scale, uncertainty, interaction, and safety, and (3) an algebraic and dynamical interaction model that supports pattern/form/model extraction and measurable effectiveness invariants. UCC classifies elements by role (Value-Adding, Archived, Communication, Evaluation, and Exchange role when transactions are first-class) using operational assignment tests and multi-role signatures. We demonstrate conditional universality under explicit modeling assumptions and show cross-domain instantiations. The structural-theory toolbox provides checklists for choosing mathematical tools (logic, probability, information, computation, optimization, symmetry, dynamics/control, games, category theory, causality, and verification). Finally, we define role-layered interaction networks and role-flow summaries that enable comparison across domains and support simulation and measurement. The manuscript includes a pilot application and specifies a multi-domain empirical validation program to establish inter-rater reliability and predictive utility. Keywords universal classification; functional roles; clustering; structural theories; multi-layer networks; dynamical systems; control theory; category theory; ecosystem modeling; simulation

Ссылка для цитирования:

Aliabdali F. 2026. A Universal Classification of Complex Systems. PREPRINTS.RU. https://doi.org/10.24108/preprints-3114603

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