Emergent Intelligence for Chaotic Supply Chain Resilience in Contested Environments

This paper introduces Vacuum Intelligence, a computational framework in which coherent, adaptive decision structure emerges from a high-entropy generative substrate rather than being imposed through explicit parameterization. The framework draws on reservoir computing principles, extended with synchronicity detection, decay-rebirth cycling, and a hypothesis-generation output layer that produces actionable logistics recommendations rather than binary threshold alerts. A prototype system is exercised against synthetic data streams modeled on the 2026 Strait of Hormuz supply chain crisis, the largest energy supply disruption in the history of the global oil market, to evaluate emergent attractor formation, early tipping-point detection, and antifragile recovery across simulated coherence-decay cycles. Results demonstrate promising behavior across all three dimensions, including progressive resilience improvement across repeated stress cycles consistent with antifragile system dynamics. Five defense application domains are developed in depth: early warning and anomaly detection from multi-source weak signals including AIS vessel tracking, satellite imagery, and open-source intelligence; resilient logistics planning under deep uncertainty; counter-sanctions and shadow-fleet disruption modeling with adaptive countermeasure hypothesis generation; antifragile command system architecture for degraded and jammed environments; and automated wargaming through large-scale internal scenario exploration cycles. The framework is positioned as a nonlinear hypothesis-generation frontend for existing human decision loops, targeted for eventual neuromorphic edge deployment on platforms including Intel Loihi 2. All scenario data is derived from publicly available reporting as of May 2026. This is exploratory conceptual research. No claims of operational readiness are advanced. External validation on sanitized or cleared logistics datasets is identified as the critical next step.