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RAD achieves state-of-the-art anomaly detection by preserving relational context and incorporating symbolic rules, outperforming traditional methods that flatten data.
Predicting adversarial actions in cyber-defense can significantly enhance the effectiveness of autonomous agents, achieving high accuracy even in partially observable environments.
