论文标题
彩色培养皿网的理论基础通过将其标记作为多分类的分析
Theoretical Foundation of Colored Petri Net through an Analysis of their Markings as Multi-classification
论文作者
论文摘要
Barwise和Seligman指出了信息流的第一个原理：“信息流是由分布式系统中的规律性产生的”。它们代表一个分布式系统，该系统由一组要分类的对象或代币组成，用于对令牌进行分类的类型以及代币和类型之间的二进制关系，该类型告诉一个令牌被分类为哪些类型的类型。我们的目标是进一步调查，并进行动态或不断发展的系统，而不是静态系统。我们声称，分类是在给定时刻或上下文中分布式系统的快照。然后，我们的目标是回答不断发展的环境提出的问题。随着上下文或配置的变化，规律性如何发展。本文是我们在\ cite {esterlin}中开始的调查的延续，在那里我们启动了如何使用Kripke结构捕获信息流动的动态。在这里，我们使用彩色培养皿网（CPN）开发相同的程序。我们首先将分类概念扩展到多分类，通过用多个关系替换令牌和类型之间的二进制关系：来自Tok（a）x typ（a）的函数到n，n，n（n（N）。为了计算其理论，多分类将分为二进制分类。事实证明，CPN的标记是多分类的。将作为CPN标记的分类的理论融合在一起，导致CPN的知识库。
Barwise and Seligman stated the first principle of information flow: "Information flow results from regularities in the distributed system." They represent a distributed system in terms of a classification consisting of a set of objects or tokens to be classified, a set of types used to classify tokens, and a binary relation between tokens and types that tells one which tokens are classified as being of which types. We aim to further this investigation and proceed with a dynamic or evolving system instead of a static system. We claim that a classification is a snapshot of a distributed system at a given moment or context. We then aim to answer the question posed by an evolving context. As the context or configuration changes, how to regularities evolve. This paper is a continuation of an investigation we started in \cite{esterlin}, where we initiated how to capture a dynamism of information flow with a Kripke structure. Here we develop the same procedure with colored Petri net(CPN). We first extend the classification concept to multiclassification by replacing its binary relation between tokens and types with a multi relation: a function from tok(A) x typ(A) to N, the set of natural numbers. The multiclassification will unfold into binary classification in order to compute its theory. It turns out that markings of a CPN are multiclassification; Amalgamating the theories of those classifications obtained as markings of CPN results in a CPN's knowledge base.
