Automated discovery of angle theorems

IF 1.2 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Annals of Mathematics and Artificial Intelligence Pub Date : 2023-05-09 DOI:10.1007/s10472-023-09841-6
Philip Todd
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引用次数: 1

Abstract

We consider geometry theorems whose premises and statement comprise a set of bisector conditions. Each premise and the statement can be represented as the rows of a “bisector matrix”: one with three non zero elements per row, one element with value -2 and the others with value 1. The existence of a theorem corresponds to rank deficiency in this matrix. Our method of theorem discovery starts with identification of rank deficient bisector matrices. Some such matrices can be represented as graphs whose vertices correspond to matrix rows and whose edges correspond to matrix columns. We show that if a bisector matrix which can be represented as a graph is rank deficient, then the graph is bicubic. We give an algorithm for finding the rank deficient matrices for a Hamiltonian bicubic graph, and report on the results for graphs with 6,8,10 and 12 vertices. We discuss a method of deriving rank deficient bisector matrices with more than 2 non-zero elements. We extend the work to matrices containing rows corresponding to angle trisectors.

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自动发现角度定理
我们考虑的几何定理,其前提和陈述包含一组等分条件。每个前提和语句都可以表示为“平分矩阵”的行:每行有三个非零元素,一个元素的值为-2,其他元素的值为1。一个定理的存在性对应于这个矩阵中的秩不足。我们的定理发现方法从秩缺等分矩阵的识别开始。一些这样的矩阵可以表示为图,其顶点对应于矩阵行,其边对应于矩阵列。我们证明了如果一个可以表示为图的等分矩阵是秩亏的,那么这个图是双三次的。给出了哈密顿双三次图的秩缺矩阵的求解算法,并给出了具有6、8、10和12个顶点的图的求解结果。讨论了非零元素多于2的缺秩等分矩阵的一种求导方法。我们将工作扩展到包含与角三分线相对应的行的矩阵。
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来源期刊
Annals of Mathematics and Artificial Intelligence
Annals of Mathematics and Artificial Intelligence 工程技术-计算机:人工智能
CiteScore
3.00
自引率
8.30%
发文量
37
审稿时长
>12 weeks
期刊介绍: Annals of Mathematics and Artificial Intelligence presents a range of topics of concern to scholars applying quantitative, combinatorial, logical, algebraic and algorithmic methods to diverse areas of Artificial Intelligence, from decision support, automated deduction, and reasoning, to knowledge-based systems, machine learning, computer vision, robotics and planning. The journal features collections of papers appearing either in volumes (400 pages) or in separate issues (100-300 pages), which focus on one topic and have one or more guest editors. Annals of Mathematics and Artificial Intelligence hopes to influence the spawning of new areas of applied mathematics and strengthen the scientific underpinnings of Artificial Intelligence.
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