ReGuard discovers network scenarios where RL controllers perform 43-64% worse than achievable and reduces those gaps by 79-85% with lightweight rule-based protection that preserves normal performance.
Testing of deep rein- forcement learning agents with surrogate models.ACM Transactions on Software Engineering and Methodology, 33(3):73:1–73:33
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Worst-Case Discovery and Runtime Protection for RL-Based Network Controllers
ReGuard discovers network scenarios where RL controllers perform 43-64% worse than achievable and reduces those gaps by 79-85% with lightweight rule-based protection that preserves normal performance.