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SCAPE reduces scenario-level prediction error by up to 34.7%, enabling safer and more efficient deployment of robot-learning policies in real-world environments.
Autonomous driving policies that ace open-loop tests can still crash and burn in the real world, because they learn to ignore the reactive nature of closed-loop environments.