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Racing on the Negative Force: Efficient Vulnerability RootCause Analysis through Reinforcement Learning on Counterexamples Dandan Xu1,2 , Di Tang3 , Yi Chen3, XiaoFeng Wang3 , Kai Chen1,2, Haixu Tang3
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Sample-efficient reinforcement learning is aimed at developing algorithms that learn optimal policies with fewer interactions with the environment, reducing the amount of data required for training.
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The report should include information on methodologies, experimental results, performance metrics, and comparisons with traditional reinforcement learning approaches.
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