Bounded Computation Under Convergence: A Provisional Reverse Nash Equilibrium Instrument for Runtime Control Within CRM-HGA

Large neural and agentic systems create a governance problem that is not reducible to accuracy, latency, or interpretability alone. A system may remain technically capable while consuming disproportionate computational resources, expanding tool or agent access, accumulating sub-threshold risk, or operating through pathways that governance cannot reconstruct in time to intervene. This paper develops Reverse Nash Equilibrium (RNE) as a provisional, separately governed computational-control instrument that can be invoked by the Concentric Resilience Mechanism and Hexagonal Governance Architecture (CRM-HGA), particularly through the Emergency Envelope Operational Protocol (EEOP). RNE is not proposed as an additional HGA function, a replacement for conventional cybersecurity, or an autonomous legitimacy engine. Its narrower purpose is to enforce a governance-defined computational envelope: model capacity may expand only when additional computation demonstrates sufficient marginal informational utility while remaining within contextual-integrity, authority, and resource boundaries. The proposal explores nested routing, activation costs, integrity penalties, cumulative-convergence signals, and an Atsumi containment posture that preserves a thick trusted core while freezing consequential writes, privilege expansion, persistence, and unbounded resource escalation. The paper distinguishes training-time differentiability from inference-time allocation, separates RNE from SCIL, ADIL, Snow White, Ma’at, ARM, and Second-Key Authority, and defines falsifiable research questions for evaluating whether bounded conditional computation can reduce resource exposure and improve traceability without unacceptable loss of task performance or edge-case fidelity. The draft further extends the RNE concept to collective-agent conditions in which effective capability may reside in relationships rather than in any single actor. It introduces provisional Distributed Strategic Emergence (DSE), Distributed Convergence Amplification (DCA), nested EEOP computational-ceiling pre-assessment, and Shadow-Actor continuity as testable governance propositions rather than established security primitives.