Meaning-State Drift and Semantic Stability Engineering: A Dynamical Framework for Internal Semantic Analysis in Autonomous Systems

This work is part of a research series on Semantic Stability Engineering (SSE) and Meaning-State Drift in autonomous systems.

Starting with the initial field claim for SSE and motivates the need for a dedicated theory of internal semantic dynamics (Zenodo DOI: 10.5281/zenodo.17635174). The previous paper provides the field definition and conceptual canon for SSE, clarifying key notions and their relationships (Zenodo DOI: 10.5281/zenodo.17711427).

In this contribution, we develop the Dynamical Semantic Drift Framework, which gives a concrete, mathematically grounded and operational treatment of internal semantic change. We formalise four core quantities:

1. Meaning-State Drift - incremental change in the system’s internal semantic organisation,
2. Coherence - short-horizon internal stability,
3. Tipping Points - abrupt transitions between semantic regimes,
4. Readability Duration - how long a meaning-state remains interpretable.

Building on these definitions, the paper introduces Semantic Stability Engineering (SSE) as a two-level framework:

Level A (Abstract Dynamics) provides a model-agnostic dynamical semantics for internal meaning-states.
Level B (Operational Measurement) defines how these quantities can be computed from encoder activations, empirical transitions and weighting profiles.

The workshop version focuses on the conceptual and operational structure of SSE and illustrates it with reinforcement-learning based case studies, showing that internal Meaning-State Drift and semantic regime shifts can occur even when external performance (e.g. reward) appears stable.

Together with the earlier field-claim and field-definition papers, this preprint is intended to serve as a reference point for future work on semantic stability, internal model dynamics, and the long-term evolution of meaning in autonomous systems.