论文标题
使用模糊数字对非单调推理的不确定性和不精确性进行建模
Modeling Uncertainty and Imprecision in Nonmonotonic Reasoning using Fuzzy Numbers
论文作者
论文摘要
为了应对推理的不确定性，已经开发了间隔值值逻辑。但是统一的间隔无法捕获间隔中不同值的信念程度的差异。为了挽救问题，三角形和梯形模糊数字与传统间隔一起用作真实价值观集。基于预订的真实和知识顺序是在定义$ [0,1] $的模糊数字集上定义的。基于这一增强的认知状态集，开发了一个答案集框架，并具有正确定义的逻辑连接剂。这种类型的框架在知识表示和推理方面具有有效的效率，在非单调环境下，规则可能会有例外的非单调环境中的含糊和不确定的信息。
To deal with uncertainty in reasoning, interval-valued logic has been developed. But uniform intervals cannot capture the difference in degrees of belief for different values in the interval. To salvage the problem triangular and trapezoidal fuzzy numbers are used as the set of truth values along with traditional intervals. Preorder-based truth and knowledge ordering are defined over the set of fuzzy numbers defined over $[0,1]$. Based on this enhanced set of epistemic states, an answer set framework is developed, with properly defined logical connectives. This type of framework is efficient in knowledge representation and reasoning with vague and uncertain information under nonmonotonic environment where rules may posses exceptions.
