Towards a Playground to Democratize Experimentation and Benchmarking of AI Agents for Network Troubleshooting

Abstract: Recent research has demonstrated the effectiveness of AI, and more specifically, LLMs, in supporting network configuration synthesis and automating network diagnosis tasks, among others. In this preliminary work, we restrict our focus to the application of AI agents to network troubleshooting and elaborate on the need for a standardized, reproducible, and open benchmarking platform, where to build and evaluate AI agents with low operational effort.