Presents the HYDRA family pattern — a universal specification for autonomous cognitive and reactive agents derived and governed by MINERVA, applicable across civilian regulated domains and any large-scale autonomous deployment. The problem: the epistemic failure of autonomous agents is structurally uniform across domains. Financial fraud detection, clinical decision support, legal document processing, and large-scale autonomous systems all share the same gap: sensor output flows directly into belief commitment without epistemic validation. The failure scales linearly with volume; human oversight degrades superlinearly. HYDRA resolves this through nine structural invariants and five correctness theorems. The cognitive/reactive holon distinction is generalized as a domain-agnostic pattern: cognitive holons handle strategic reasoning and mission planning; reactive holons execute with fast HTN cycles and real-time EVR validation. MINERVA derives and governs HYDRA instances through signed MissionPackages that encode pre-verified plan libraries, validated belief states, and normative constraints. Validated instantiations: HYDRA-Documental (legal document processing), HYDRA-Extractor (Azure DI integration), HYDRA-ExtractorEntidades (entity extraction). Compared against six systems (Maven, Gospel, AutoGen, CrewAI, LangGraph, Jason) across nine architectural dimensions spanning civilian regulated deployments and large-scale autonomous systems. HYDRA is the only framework that simultaneously satisfies epistemic correctness, scale invariance, formal auditability, and structural human authority over irreversible actions.
Jaime et al. (2026) studied this question.