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English(EN) Learning Size Independent Constraint Models from Input Data and Positive and Negative Example Solutions

新工具可根据数据生成与大小无关的约束模型

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种约束获取工具（Constraint Acquisition Tool），能够从示例解和输入数据生成与大小无关的约束程序。该工具可以识别典型的约束模式并将其泛化为可应用于新数据集的模型。该系统以MiniZinc语言输出代码，并提供所生成模型的文本描述。其有效性在PTHG21挑战赛的问题上得到了验证，证实了该方法的有效性。 AI

影响 这项研究有望提高约束编程在各种问题解决领域的效率和适用性。

排序理由 该集群包含一篇描述新约束建模方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新工具可根据数据生成与大小无关的约束模型

本文如何被排名

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Tool
该集群包含一篇描述新约束建模方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
paper, other
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High
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完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Helmut Simonis ·

    从输入数据和正负示例解中学习尺寸无关的约束模型

    arXiv:2610.13640v1 Announce Type: new Abstract: In this paper we describe a Constraint Acquisition Tool that generates size independent constraint programs from input data and positive and negative example solutions of multiple problem instances. The system finds size specific mo…

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