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May 15, 2026Open Access

TDH–UHR.roi: A Unified Hybrid Regime Framework for Survivability Dynamics, Adaptive Intelligence, and Executable System Control (Version 1.0)

Key Points

The framework aims to model survivability dynamics in complex hybrid systems using a unified approach.
Introduces a generalized framework integrating state evolution and recursive memory.
Presents compressed mathematical equations to ensure clarity and maintain full reconstructibility.
Applies the framework to various domains including artificial intelligence and ecological modeling.
Supports simulation, monitoring, and adaptive control within hybrid systems.
Emphasizes structural clarity and mathematical consistency for practical applications.
Sets the foundation for future computational implementation and empirical validation.

Abstract

Title TDH–UHR.roi: A Unified Hybrid Regime Framework for Survivability Dynamics, Adaptive Intelligence, and Executable System Control (Version 1.0) Authors Hau Dinh Thai (Pen-names: TDH, or Thoriel-TDH) Collaborator ChatGPT (OpenAI) Description (Abstract) TDH–UHR.roi (Unified Hybrid Regime Theory, Regular Optimized Integrity) introduces a generalized framework for modeling survivability dynamics in complex hybrid systems. The theory integrates state evolution, recursive memory, entropy–coherence interaction, adaptive intelligence, and governance control into a unified structure. A compressed set of core equations is presented to preserve clarity while maintaining reconstructibility of the full theoretical system. The framework supports simulation, monitoring, and adaptive control, with applications in artificial intelligence, infrastructure systems, ecological modeling, and socio-technical environments. Version 1.0 emphasizes structural clarity, mathematical consistency, and application readiness, providing a foundation for future computational implementation, simulation, and empirical validation. Keywords Hybrid Systems Survivability Dynamics Adaptive Systems Complex Systems Artificial Intelligence System Control Resilience Engineering Multi-Agent Systems Information Dynamics Systems Theory Network Dynamics Computational Modeling Version 1.0 Publication Date 2026-05-12 Notes This Version 1.0 release adopts a compressed mathematical representation strategy, presenting only a minimal set of core equations to ensure clarity and accessibility. A more comprehensive mathematical formulation, including extended derivations and simulation-ready structures, is reserved for future versions. Communities Physics Mathematics Artificial Intelligence Systems Theory

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