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Agentic AI Empowered Intent-Based Networking for 6G

Published: 2026-01-19 · Source: ARXIV · Tier: 2 · Confidence: candidate · Score: 3
Original: https://arxiv.org/abs/2601.06640v1

Abstract

Why this matters

As telecom networks evolve toward Level-4 autonomy, intent-based interfaces are increasingly proposed as the abstraction layer between human objectives and autonomous control loops. This paper explores how **agentic AI architectures** can operationalize intent-based networking in future 6G environments.

Rather than treating intent as a static configuration translation problem, the authors frame intent handling as a **goal-oriented reasoning process**, where agents interpret, decompose, and adapt intents across dynamic network conditions.

Key contribution

- Proposes an **agent-centric architecture** for intent interpretation and execution
- Positions intent-based networking as a **continuous decision process**, not a one-time translation
- Discusses applicability to **closed-loop control**, orchestration, and cross-domain coordination
- Aligns with emerging telecom autonomy narratives (SMO, policy-driven control, adaptive assurance)

Limitations and cautions

- The work remains largely **conceptual** and simulation-driven
- Accountability, traceability, and safety assurance mechanisms are not fully specified
- Practical deployment constraints (latency, determinism, governance) are acknowledged but unresolved

Autonomy Atlas assessment

This paper is relevant as a **directional signal** rather than a deployable blueprint.
It helps frame how agentic reasoning may sit above traditional control loops, but should be read alongside **standards-based and operations-grounded references**.

**Status:** Published as contextual insight, not normative guidance.