This document proposes a closure-based judgment framework for Artificial General Intelligence within the SΔϕ Formalism. Rather than treating AGI as a vague destination, a matter of human equivalence, or a benchmark-based label, this paper reformulates AGI as a structured closure problem. Within SΔϕ, intelligence is not treated as a static possession, but as a phase-stabilized capacity for maintaining coherent transition across heterogeneous tasks, environments, and recursive updates. On this basis, AGI is evaluated not by appearance or rhetoric, but by the degree to which a minimal set of operational conditions has become closed. This paper introduces five minimal closure criteria for AGI judgment: Global Generality Long-Horizon Recursive Agency World-Model Correspondence Self-Updating Robustness Creative Path Generation Each criterion is presented as a closure condition within a Δϕ-based operational ontology, rather than as a symbolic philosophical ideal. Version 1.1 includes an applied mapping example for the GPT family as of March 2026, asking not whether AGI has simply “arrived,” but which operational conditions appear relatively closed, which remain partially open, and which are still structurally far from closure. The aim of this document is not to declare AGI achieved or unachieved in absolute terms, but to provide a principled judgment framework for evaluating AGI-relevant closure patterns.
Sofience (Wed,) studied this question.