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English(EN) A Fast Model Counting Algorithm for Two-Variable Logic with Counting and Modulo Counting Quantifiers

新算法加速两变量逻辑的AI模型计数

研究人员开发了一种名为 IncrementalWFOMC3 的新算法,该算法专为带计数量词的两变量逻辑片段($\mathbf{C}^2$)及其模计数扩展($\mathbf{C}^2_{\text{mod}}$)内的加权一阶模型计数(WFOMC)而设计。该算法直接在 Scott 标准型上操作,避免了先前方法中使用的量词消除约简的开销。新方法在 $\mathbf{C}^2$ 中实现了更紧密的 WFOMC 数据复杂度界限,并证明了 $\mathbf{C}^2_{\text{mod}}$ 的域可提升性,与现有算法相比,运行时长有了显著提高。 AI

影响 引入了一种更有效的提升概率推理算法,有望提高依赖逻辑推理和模型计数的AI系统的性能。

排序理由 这是一篇详细介绍特定逻辑片段新算法的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新算法加速两变量逻辑的AI模型计数

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这是一篇详细介绍特定逻辑片段新算法的研究论文。[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) · Shixin Sun, Astrid Klipfel, Ond\v{r}ej Ku\v{z}elka, Yuanhong Wang, Yi Chang ·

    一种带有计数和模计数量词的两变量逻辑的快速计数算法

    arXiv:2605.03391v1 Announce Type: cross Abstract: Weighted first-order model counting (WFOMC) is a central task in lifted probabilistic inference: It asks for the weighted sum of all models of a first-order sentence over a finite domain. A long line of work has identified domain-…