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English(EN) Using ASP(Q) to Handle Inconsistent Prioritized Data

研究人员探索使用 ASP(Q) 查询不一致的优先级数据

研究人员开发了一种使用带量词的答案集编程 (ASP(Q)) 来管理不一致的优先级数据的新方法。该方法定义了三种类型的最优修复——帕累托最优、全局最优和完成最优——以根据其优先级处理冲突事实。该论文介绍了基于全局最优修复语义的首次实现以及一种称为接地语义的可处理的近似方法,实验结果证明了它们的可行性和影响。 AI

影响 引入了解决数据不一致性的新颖计算技术,可能影响知识表示和推理系统。

排序理由 这是一篇关于处理不一致数据的新计算方法的学术论文。

在 arXiv cs.AI 阅读 →

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研究人员探索使用 ASP(Q) 查询不一致的优先级数据

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这是一篇关于处理不一致数据的新计算方法的学术论文。
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Giuseppe Mazzotta ·

    使用ASP(Q)处理不一致的优先级数据

    We explore the use of answer set programming (ASP) and its extension with quantifiers, ASP(Q), for inconsistency-tolerant querying of prioritized data, where a priority relation between conflicting facts is exploited to define three notions of optimal repairs (Pareto-, globally- …