A T-API-Compliant ReAct Agentic Loop for Optical Networks: Generic vs. Domain-Specific Tool Abstractions
arXiv:2606.18000v1 Announce Type: cross Abstract: Optical networks need intent-driven, closed-loop agentic management, a key enabler for higher autonomy levels. We present the first T-API-compliant reasoning and act (ReAct) loop. We show that domain-specific composite tools achieve 90% oracle-validated correctness with threefold token savings compared to generic tools.
The increasing complexity and scale of optical networks require more autonomous management, aligning with the rapid advancements in AI agentic systems.
This development indicates a tangible application of AI agents in critical infrastructure, promising significant efficiency gains and higher autonomy levels for network management.
Network operations can become more intent-driven and automated, potentially reducing human intervention and latency in managing optical networks.
- · Telecommunications companies
- · AI agent developers
- · Network equipment manufacturers
- · Legacy network management solution providers
- · Manual network operations teams
Increased efficiency and reliability of optical network management through AI-driven automation.
Accelerated deployment of new network services and adaptation to changing traffic demands.
Shift in human roles in network operations towards supervision and strategic planning rather than manual configuration and troubleshooting.
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Read at arXiv cs.AI