不确定条件下基于规则推理的鲁棒逻辑

S. Parsons, M. Kubát, M. Dohnal
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引用次数: 1

摘要

基于粗糙集的概念,提出了一种用于不确定推理的符号量化逻辑。这个数学模型为一个健壮的推理系统提供了一个简单而可靠的基础。本文描述了一个类似于命题式的推理规则,并展示了推理系统如何使用它来确定不确定知识条件下最可能的结果。对基于规则的推理中逻辑的鲁棒性进行了分析
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A robust logic for rule-based reasoning under uncertainty
A symbolically quantified logic is presented for reasoning under uncertainty that is based upon the concept of rough sets. This mathematical model provides a simple yet sound basis for a robust reasoning system. A rule of inference analogous to modus ponens is described, and it is shown how it might be used by a reasoning system to determine the most likely outcome under conditions of uncertain knowledge. An analysis of the robustness of the logic in rule-based reasoning is also presented.<>
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