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From Automated to Autonomous: Hierarchical Agent-native Network Architecture (HANA)

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arXiv:2605.20608v1 Announce Type: new Abstract: Realizing Level 4/5 Autonomous Networks (AN) demands a shift from static automation to agent-native intelligence. Current operations, reliant on rigid scripts, lack the cognitive agency to handle off-nominal conditions. To address this, this letter proposes a hierarchical multi-agent reference architecture enabling high-level autonomy. The framework features a Dual-Driven Orchestrator that coordinates specialized Executive Agents, supported by a shared Public Memory for unified domain knowledge. A key innovation is the integration of agent self-awareness, which empowers the system to harmonize deliberative strategic governance with reflexive fault recovery. We instantiate and validate this architecture within a 5G Core environment. Case studies demonstrate that the system sustains critical throughput under congestion and reduces Mean Time to Repair (MTTR) by 86%, confirming its efficacy in unifying strategic planning with operational resilience.

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Topic: From Automated to Autonomous: Hierarchical Agent-native Network Architecture (HANA)
Source website: arxiv.org
Publication date at source: 2026-05-22
Collection date on DzCademia: 2026-05-22

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intelligence artificielle réseau autonome architecture hiérarchique autonomie

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From Automated to Autonomous: Hierarchical Agent-native Network Architecture (HANA)

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