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S-AI-CITY: EXPERIMENTAL EVALUATION OF HORMONAL URBAN ORCHESTRATION

Sep 2026 · International Journal of Artificial Intelligence & Applications · 0 citations · 8 references

Abstract

S-AI-CITY is a first-generation hormonal orchestration framework for urban intelligence in which heterogeneous urban observations are transformed by six Gland Agents into a shared regulatory state composed of Mobilin, Energexin, Environin, Resiliencin, Normin, and Servicin. Article I introduced the architecture, while Article II formalized its multi-layer urban graph, reaction-diffusion hormonal dynamics, 24 specialized agents, sparse constrained orchestration, hierarchical Zone → District → City organization, and symbolic Urban Engram memory. The present Article III defines the empirical evaluation stage of the trilogy. The study is organized around the SAI-UT+ CITY testbench and twelve parameterized urban scenario families spanning nominal operation, sector-specific stress, multi-domain disturbances, cascading failures, degraded communication, missing data, recovery, and recurrent events. The evaluation compares S-AI-CITY with a ladder of non-hormonal, rule-based, learned, model-based, random-budget, and offline-oracle references under matched quality-of-service and safety conditions. Decision quality, parsimony, operational cost, hormonal reactivity, cross-domain coordination, resilience, memory acceleration, explainability, constraint satisfaction, robustness, and scalability are evaluated jointly. The experimental design is explicitly falsifiable: each major architectural mechanism is associated with a null hypothesis and a corresponding ablation, and no benefit is attributed to a mechanism when its removal produces statistically indistinguishable behavior under matched conditions. Particular attention is given to avoiding circular validation by separating the scenario generator from the hormonal model and to preventing tuning asymmetry across competing methods. The resulting protocol is intended to determine not only whether S-AI-CITY can provide measurable operational advantages, but also which mechanisms produce those advantages, under which urban regimes they persist, and where they become negligible or disappear

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