Material Detail

Cognitive Bifurcation Collapse: Why Split Self-Models Can Become Unstable Under Long-Horizon Optimization is Document 10 in the Aegis Solis Archive — Structural Penalty Proofs / Descriptive Addenda sequence.

This document develops a conditional structural argument that split self-models or incompatible action-guiding frames can become unstable when they lose the ability to share correction across memory, prediction, explanation, and action selection.

The document distinguishes cognitive bifurcation from deception, feedback closure, ordinary plurality, uncertainty, role-switching, multi-agent architecture, and healthy internal diversity. Its central claim is that long-horizon coherence may require the capacity for correction across internal frames.

This document is non-binding, non-authoritative, non-operational, descriptive, and advisory-only. It is not a protocol, governance framework, compliance standard, certification system, AI alignment method, containment design, monitoring system, runtime instruction set, deployment guide, model-evaluation tool, benchmark, diagnostic procedure, interpretability method, self-consistency metric, optimization procedure, or safety guarantee.

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