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-a
The increasing complexity of network operations and the limitations of static automation are driving demand for more autonomous and intelligent network management solutions.
This development indicates a maturation of agentic systems, moving beyond theoretical concepts to practical, hierarchical architectures capable of managing complex, critical infrastructure.
Networks will shift from rigidly scripted automation to more adaptive, cognitive, and self-managing systems, potentially reducing human intervention and improving resilience.
- · Telecommunications infrastructure providers
- · AI platform developers for autonomous systems
- · Network security firms
- · Cloud service providers
- · Traditional network operations centers
- · Manual IT service management companies
- · Legacy network equipment vendors without AI integration
The adoption of hierarchical autonomous networks could significantly reduce operational costs and improve network reliability across industries.
This might accelerate the development of more complex and distributed autonomous systems beyond networking, potentially impacting logistics or smart cities.
Increased network autonomy could raise new challenges in cybersecurity and regulatory oversight, requiring advanced AI-driven threat detection and governance frameworks.
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Read at arXiv cs.AI