Governed Shared Memory for Multi-Agent LLM Systems
Multi-agent LLM environments require robust mechanisms for shared knowledge management. This paper formalizes the fleet-memory problem and identifies four foundational failure modes: unauthorized leakage, stale propagation, contradiction persistence, and provenance collapse. To address these, we define explicit systems-level primitives: scoped retrieval, temporal supersession, provenance tracking, and policy-governed memory propagation. These primitives are implemented in MemClaw, a production m
Record details
Published: 23 June 2026
Source: arXiv
Category: Research
Topics: Regulation · Privacy · Agents & autonomy · Environment
Retrieved: 14 July 2026
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ethics.ai (23 June 2026), “Governed Shared Memory for Multi-Agent LLM Systems,” evidence record 652, https://ethics.ai/record/652 (originally published by arXiv).
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