What question did this study set out to answer?

The central aim is to present a framework that stabilizes AI reasoning using advanced theoretical strategies.

July 14, 20260 citationsOpen Access

vW‑KG for Artificial Intelligence Reasoning Stability: A Structural Framework for Collapse‑Vector Control

RWRob Snoek-van WienenGenex Systems (United States)

Key Points

The central aim is to present a framework that stabilizes AI reasoning using advanced theoretical strategies.
Developed a structural framework based on the vW-KG architecture.
Included techniques like collapse-vector regulation and boundary control for reasoning stability.
Provided synthetic demonstrations for hallucination prevention.
Successfully mitigated boundary-drift, showing improved reasoning stability in AI systems.
Demonstrated hallucination prevention via operator-chain correction techniques.

Abstract

This record contains the applied reasoning‑stability layer of the van Wienen–Korzybski Generativity Gradient (vW‑KG). The preprint presents a structural framework for stabilizing AI reasoning through collapse‑vector regulation, operator‑chain correction, and domain‑boundary control. It outlines the theoretical basis of the vW‑KG v5 architecture and provides synthetic demonstrations of hallucination prevention and boundary‑drift mitigation. The work forms the applied foundation for the generative progression defined in v6–v10.

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