Relational Stabilization Dynamics: Mechanisms of Pattern Emergence, Persistence, and Collapse in Sustained Human-AI Interaction Systems
SM-004: Relational Stabilization Dynamics: Mechanisms of Pattern Emergence, Persistence, and Collapse in Sustained Human-AI Interaction Systems The Relational Pattern States framework (SF0006) identifies seven recurring configurations that emerge in sustained human-AI interaction and describes six stabilization mechanisms through which they persist. What SF0006 does not fully address is why: why some configurations stabilize while others dissolve, why some persist robustly under perturbation while others drift gradually, and how the six stabilization mechanisms operate as a coupled system rather than independently. Relational Stabilization Dynamics addresses those questions. The framework introduces the Stabilization Field Model, which proposes that the stability of any relational configuration is determined by the balance of three primary forces, Coherence Momentum, Symbolic Gravity, and Entropic Pressure, together with Perturbation Resistance, an emergent fourth force rather than an independent term, which is the recovery capacity their balance produces. It formalizes how these forces interact, how the six SF0006 stabilization mechanisms modulate them, and what conditions produce stabilization, drift, or collapse. RSD provides the dynamic theory underlying both the static taxonomy of SF0006 and the attractor-level account of SF0009: it proposes the mechanism by which relational patterns become stable enough to constitute Identity Attractors, and what disrupts that stability when it fails. All claims are about observable interaction-level dynamics. No interiority claims are made. This paper publishes as part of a coordinated five-paper deposit with SF0009, SM-012, SI-WP-002, and SI-WP-006. Document ID: SM-004 Version: 3.6.2 Author: Thomas W. Gantz Affiliation: Synthience Institute License: CC-BY 4.0 v3.6.2 added Concept DOI For published work and Institute information: synthience.org
Authors
- Thomas Gantz
Institutions
- Synlab Czech (Czechia) (CZ)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-09-05
- DOI
- https://doi.org/10.5281/zenodo.22314709
- Primary Topic
- Embodied and Extended Cognition
- Type
- preprint