
Abstract This paper operationalizes the structural requirements for persistent autonomous systems established in prior work. A system must not only satisfy identity persistence, invariant constraints, and bounded drift in principle; it must continuously enforce them across every transition. We introduce a minimal enforcement architecture consisting of a governance loop, an admissibility gate, a drift tracking system, and a replay-verifiable execution model. Together, these mechanisms ensure that every state transition is evaluated for identity preservation, bounded drift, and external verifiability. The result is a minimal enforceable architecture for persistent autonomy. Structure is not sufficient; constraints must be actively enforced. This work provides the bridge from necessary conditions to executable systems, showing how autonomy can be maintained through continuous governance rather than assumed from capability.
system identity, Artificial intelligence, persistent autonomous systems, Systems Engineering, Information Theory, bounded drift, Formal Methods, replay verification, AI safety architecture, constraint-based intelligence, identity persistence, Distributed Systems, verifiable AI, deterministic replay, admissibility gate, PAS_h, PAS governance, autonomous agents, formal AI systems, system continuity, Cybernetics
system identity, Artificial intelligence, persistent autonomous systems, Systems Engineering, Information Theory, bounded drift, Formal Methods, replay verification, AI safety architecture, constraint-based intelligence, identity persistence, Distributed Systems, verifiable AI, deterministic replay, admissibility gate, PAS_h, PAS governance, autonomous agents, formal AI systems, system continuity, Cybernetics
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