This preliminary work highlights the effectiveness of AI agents in troubleshooting networks, suggesting a standardized benchmarking platform for evaluation.
Recent research has demonstrated the effectiveness of Artificial Intelligence (AI), and more specifically, Large Language Models (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.
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Wang et al. (2025) studied this question.
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