论文标题

使用丰富的负面信息分类

Categorification of Negative Information using Enrichment

论文作者

Censi, Andrea, Frazzoli, Emilio, Lorand, Jonathan, Zardini, Gioele

论文摘要

在许多工程应用中,推理“负面信息”很有用。例如,在计划问题中,提供最佳解决方案与给出可行的解决方案(“正面”信息)以及证明没有比给出的解决方案更好的解决方案(“负”信息)相同。我们通过引入“偏态”的概念而不是形态学的积极信息来对负面信息进行建模。 “ Nategory”是一个具有“ NOM”集以外的类别,除了HOMSETS之外,并指定了偶然性与形态之间的相互作用。特别是,我们有形式形式的构图规则 +偏射$ \ to $ norphism。千边形不会自己构成;相反,他们将形态主义用作催化剂。在提供了几个应用示例之后,我们将NATEGIRE与丰富的类别理论联系起来。具体而言,我们证明了富含De Paiva的辩证类别GC的类别,在C = SET并配备了修改的单体产品的情况下,定义了满足其他规则性属性的Negation。这以使负面和积极的态度平等公民的方式进行了正式的负面信息。

In many engineering applications it is useful to reason about "negative information". For example, in planning problems, providing an optimal solution is the same as giving a feasible solution (the "positive" information) together with a proof of the fact that there cannot be feasible solutions better than the one given (the "negative" information). We model negative information by introducing the concept of "norphisms", as opposed to the positive information of morphisms. A "nategory" is a category that has "nom"-sets in addition to hom-sets, and specifies the interaction between norphisms and morphisms. In particular, we have composition rules of the form morphism + norphism $\to$ norphism. Norphisms do not compose by themselves; rather, they use morphisms as catalysts. After providing several applied examples, we connect nategories to enriched category theory. Specifically, we prove that categories enriched in de Paiva's dialectica categories GC, in the case C = Set and equipped with a modified monoidal product, define nategories which satisfy additional regularity properties. This formalizes negative information categorically in a way that makes negative and positive morphisms equal citizens.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源