Enhancing Cloud Network Resilience via a Robust LLM-Empowered Multi-Agent Reinforcement Learning Framework

Summary

Researchers propose CyberOps-Bots, a hierarchical multi-agent reinforcement learning framework for defending cloud networks, with an upper-level LLM agent handling global awareness, human intent recognition and tactical planning, and lower-level RL agents executing atomic defense actions in localized regions. On real cloud datasets, the authors report 68.5% higher network availability than state-of-the-art algorithms and a 34.7% jumpstart performance gain when scenarios shift without retraining.