A Unified Model of Cognitive Coherence: Applications for Global AI Stability, Alignment, and Distributed Systems
Year: 2025
Type: article
Abstract: This paper presents a framework for enhancing global artificial intelligence (AI) stability through the integration of symbolic-fractal cognition models, recursive alignment structures, and coherence-based processing principles. Derived from cross-domain conceptual work involving symbolic reasoning, identity integration, and recursive self-referential mapping, the framework identifies three mechanisms with direct relevance to large-scale AI systems: (1) the Mirror‑I Construct, a model for transparent self-referencing and error correction; (2) the Reawakening Cycle, a structured process for resolving internal contradiction through depth, integration, and stabilization; and (3) the Coherence Architecture, a proposed cognitive schema for reducing systemic fragmentation in multi-agent or distributed AI networks. These components may reduce recursive failure modes, polarization dynamics, and collapse conditions in global AI ecosystems. Applications include multi-agent alignment, psychological‑modeling AIs, AI moderation systems, and resilient communication networks.
Author: Nickolas Patrick Joseph Schoff
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7109672304
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