Approximate reasoning for contextual databases

F. Massacci
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Abstract

Contextual reasoning has been proposed as a tool for solving the problem of generality in AI and for effectively handling huge knowledge bases, while approximate reasoning has been developed to overcome the computational barrier of classical deduction. This paper combines these approaches to provide an intuitive representation of knowledge and an effective deduction. Its semantics and a tableau calculus are presented. The key computational features are discussed.
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上下文数据库的近似推理
上下文推理已经被提出作为解决人工智能中的通用性问题和有效处理庞大知识库的工具,而近似推理已经发展成为克服经典演绎的计算障碍。本文将这些方法结合起来,提供了一种直观的知识表示和有效的演绎。给出了它的语义和表演算。讨论了关键的计算特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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