[2603.20833] Governance-Aware Vector Subscriptions for Multi-Agent Knowledge Ecosystems

Computer Science > Artificial Intelligence arXiv:2603.20833 (cs) [Submitted on 21 Mar 2026] Title:Governance-Aware Vector Subscriptions for Multi-Agent Knowledge Ecosystems Authors:Steven Johnson View a PDF of the paper titled Governance-Aware Vector Subscriptions for Multi-Agent Knowledge Ecosystems, by Steven Johnson View PDF HTML (experimental) Abstract:As AI agent ecosystems grow, agents need mechanisms to monitor relevant knowledge in real time. Semantic publish-subscribe systems address this by matching new content against vector subscriptions. However, in multi-agent settings where agents operate under different data handling policies, unrestricted semantic subscriptions create policy violations: agents receive notifications about content they are not authorized to access. We introduce governance-aware vector subscriptions, a mechanism that composes semantic similarity matching with multi-dimensional policy predicates grounded in regulatory frameworks (EU DSM Directive, EU AI Act). The policy predicate operates over multiple independent dimensions (processing level, direct marketing restrictions, training opt-out, jurisdiction, and scientific usage) each with distinct legal bases. Agents subscribe to semantic regions of a curated knowledge base; notifications are dispatched only for validated content that passes both the similarity threshold and all applicable policy constraints. We formalize the mechanism, implement it within AIngram (an operational multi-agent kno...