数学文本的逻辑模型:零除法的约定案例

IF 0.7 3区 数学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Logic Language and Information Pub Date : 2024-07-13 DOI:10.1007/s10849-024-09420-w
Jan A. Bergstra, John V. Tucker
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引用次数: 0

摘要

涉及除法的算术课文都有一些约定俗成的规则,以避免出现与零除法(DbZ)有关的问题。我们给出了一个基本算术文本的模型,并借助许多示例和反例,对可称为除以零(DbZ)的传统约定进行了部分描述。我们引入了合法和非法文本的非正式概念来分析这些惯例。首先,我们证明了文本的合法性在算法上是不可判定的。因此,我们知道并不存在一套简单、合理和完整的准则来明确决定如何避免 DbZ。我们认为,这些观察结果要求我们进一步探索数学惯例。我们提出了一种利用逻辑学来推进合法与非法分析的方法:模型中的算术文本可以转化为特殊总体代数上的逻辑公式,而特殊总体代数能够在总体世界中近似于局部性。我们所使用的代数方程被称为 "共同草地"。我们用形式化的方法深入到非正式的数学实践中,提出了关于 DbZ 的问题,我们将在最后讨论这些问题。
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Logical Models of Mathematical Texts: The Case of Conventions for Division by Zero

Arithmetical texts involving division are governed by conventions that avoid the risk of problems to do with division by zero (DbZ). A model for elementary arithmetic texts is given, and with the help of many examples and counter examples a partial description of what may be called traditional conventions on DbZ is explored. We introduce the informal notions of legal and illegal texts to analyse these conventions. First, we show that the legality of a text is algorithmically undecidable. As a consequence, we know that there is no simple sound and complete set of guidelines to determine unambiguously how DbZ is to be avoided. We argue that these observations call for further explorations of mathematical conventions. We propose a method using logics to progress the analysis of legality versus illegality: arithmetical texts in a model can be transformed into logical formulae over special total algebras that are able to approximate partiality but in a total world. The algebras we use are called common meadows. Our dive into informal mathematical practice using formal methods opens up questions about DbZ which we address in conclusion.

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来源期刊
Journal of Logic Language and Information
Journal of Logic Language and Information COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEL-LOGIC
CiteScore
1.70
自引率
12.50%
发文量
40
期刊介绍: The scope of the journal is the logical and computational foundations of natural, formal, and programming languages, as well as the different forms of human and mechanized inference. It covers the logical, linguistic, and information-theoretic parts of the cognitive sciences. Examples of main subareas are Intentional Logics including Dynamic Logic; Nonmonotonic Logic and Belief Revision; Constructive Logics; Complexity Issues in Logic and Linguistics; Theoretical Problems of Logic Programming and Resolution; Categorial Grammar and Type Theory; Generalized Quantification; Information-Oriented Theories of Semantic Structure like Situation Semantics, Discourse Representation Theory, and Dynamic Semantics; Connectionist Models of Logical and Linguistic Structures. The emphasis is on the theoretical aspects of these areas.
期刊最新文献
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