Beyond State Machines: Executing Network Procedures with Agentic Tool-Calling Sequences
Learn how to execute network procedures using Agentic Tool-Calling Sequences with LLM-based network AI agents, enabling flexible and customized services in mobile communication systems
- Utilize LLM-based network AI agents to execute network procedures
- Express network procedures as sequences of tool invocations
- Investigate four approaches to Agentic Tool-Calling Sequences
- Evaluate the performance of each approach in executing network procedures
- Implement the most effective approach in a real-world network setting
Network engineers and AI researchers can benefit from this approach to automate complex network operations and drive autonomous decision-making across the network. This can improve the efficiency and reliability of network services.
💡 LLM-based network AI agents can be used to execute network procedures as sequences of tool invocations, enabling flexible and customized services in mobile communication systems
🚀 Execute network procedures with Agentic Tool-Calling Sequences using LLM-based network AI agents! #AI #NetworkAutomation
Key Takeaways
Learn how to execute network procedures using Agentic Tool-Calling Sequences with LLM-based network AI agents, enabling flexible and customized services in mobile communication systems
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Abstract:
arXiv:2605.02584v1 Announce Type: cross Abstract: Agentic AI will be an essential enabling technology for designing future mobile communication systems, which could provide flexible and customized services, automate complex network operations, and drive autonomous decision-making across the network. This work studies how Large Language Model (LLM)-based network AI agents can be utilized to execute network procedures expressed as sequences of tool invocations. We investigate four approaches, whic
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