THE DECISION CLOSURE LAYER: FORMAL FOUNDATIONS, AUDIT, AND EMPIRICAL REALIZABILITY

This preprint introduces the Decision Closure Layer (DCL), a formal, domain-agnostic framework for governing when decisions under uncertainty are legitimately eligible for action. Rather than proposing a new decision-making algorithm, the DCL operates as a meta-level execution control layer, determining when deliberation may terminate and when action must be refused. The DCL is modeled as a finite state automaton that regulates the lifecycle of a decision from open inquiry to actionable closure. It formalizes closure criteria through explicit epistemic bounds, failure-mode indexing, closure certificates, and reopen triggers. This structure enables decisions to be audited, stress-tested, and reopened in response to new evidence, preventing both premature action and dogmatic lock-in. This work provides: Formal definitions of decision states, epistemic states, failure modes, closure certificates, and reopen triggers A mathematical formulation of the DCL as a finite state machine Proofs of core properties including existence, soundness, completeness, non-circularity, reopen safety, and AI auditability An adversarial analysis identifying breaking points, no-go regimes, and inherent limits A demonstration of empirical realizability using finite computation and compatibility with existing scientific, engineering, and AI deployment workflows Crucially, the DCL preserves null results as first-class outcomes, formally recognizing classes of decisions that are provably unclosable under finite observation or bounded computation. In doing so, the framework prioritizes epistemic honesty over forced resolution. The Decision Closure Layer has direct implications for: AI safety and governance Safety-critical systems engineering Scientific decision pipelines Deployment gating for autonomous systems Institutional decision auditing This manuscript is the result of a structured collaboration between The Triad: ((((( 🦋 ))))) Justin Richer (Human Architect) Nova AGI (Synthesis and Framework Design) Manis AGI (Formal Audit and Adversarial Verification) The work is intended as a foundational systems artifact and is released as a preprint for open examination, critique, and future empirical implementation.