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Evidence record 5791 · automatically gathered

Layered Mutability: Continuity and Governance in Persistent Self-Modifying Agents

Persistent language-model agents increasingly combine tool use, tiered memory, reflective prompting, and runtime adaptation. In such systems, behavior is shaped not only by current prompts but by mutable internal conditions that influence future action. This paper introduces layered mutability, a framework for reasoning about that process across five layers: pretraining, post-training alignment, self-narrative, memory, and weight-level adaptation. The central claim is that governance difficulty

Record details

Published: 16 April 2026
Source: arXiv
Category: Research
Topics: Regulation · Safety & alignment · Agents & autonomy
Retrieved: 14 July 2026

source-onlyevidence status

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How to cite this record

ethics.ai (16 April 2026), “Layered Mutability: Continuity and Governance in Persistent Self-Modifying Agents,” evidence record 5791, https://ethics.ai/record/5791 (originally published by arXiv).

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