AGI-CNS / L(6+7): Cognitive Artificial Intelligence as Constrained Realization of Stable Action Branches within the L(6+7) Framework

This manuscript formulates AGI-CNS as a science-philosophical and implementation-agnostic architecture for cognitive artificial intelligence within the L(6+7) framework. The central thesis is that future AI should not be modeled primarily as answer generation, but as constrained realization of admissible stable action branches. The framework is derived as a cognitive reduction of the L(6+7) corpus: internal state-response geometry, stable histories, entropic time, Observer Gate, measurable self-view, residual-ledger discipline, cognitive resonance, system-system synchronization, and safety membrane.

The work does not claim completed AGI, machine consciousness, a controllable observer effect, or disclosure of any industrial implementation. Its contribution is a formal architecture, a minimal calculation model, a validation protocol for future cognitive decision systems, and a public reproducibility package.

Contribution note: The author gratefully acknowledges Konstantin Olegovich Zigangirov for discussions, assistance in organizing the source materials, and support in manuscript preparation. The theoretical formulation, mathematical development, and final scientific claims of the present paper remain the responsibility of the author.