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新方法为NP难问题生成难题

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种新颖的方法来生成优化问题的挑战性实例，将实例创建本身视为一项优化任务。该方法使用黑盒优化器来搜索最大化求解器运行时间的实例，仅需要求解器、实例编码器和计算预算。该方法成功应用于四个NP难问题，包括可满足性问题和旅行商问题，生成的实例比随机抽样生成的实例难得多，并且与精心挑选的基准集相当。 AI

影响 该方法可以通过确保AI模型在真正具有挑战性的问题实例上进行测试来提高其评估的可靠性。

排序理由 该条目是一篇学术论文，详细介绍了一种为优化问题生成难题的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新方法为NP难问题生成难题

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该条目是一篇学术论文，详细介绍了一种为优化问题生成难题的新方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Jamie Fravel, Martin Kouteck\'y, Pavlo Tsitsei ·

    按需生成难题

    arXiv:2610.22637v1 Announce Type: cross Abstract: The conclusions of an experimental study of algorithms are only as good as the instances they are run on. Benchmark libraries for well-studied problems took decades to curate, while evaluations of new problems often fall back on r…

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