{"title":"创建新的几何证明问题的程序","authors":"Philip Todd, Danny Aley","doi":"10.1007/s10472-023-09854-1","DOIUrl":null,"url":null,"abstract":"<div><p>In a previous paper Todd (Submitted to AMAI, 2022), linear systems corresponding to sets of angle bisector conditions are analyzed. In a system which is not full rank, one bisector condition can be derived from the others. In that paper, we describe methods for finding such rank deficient linear systems. The vector angle bisector relationship may be interpreted geometrically in a number of ways: as an angle bisector, as a reflection, as an isosceles triangle, or as a circle chord. A rank deficient linear system may be interpreted as a geometry theorem by mapping each vector angle bisector relationship onto one of these geometrical representations. In Todd (Submitted to AMAI, 2022) we illustrate the step from linear system to geometry theorem with a number of by-hand constructed examples. In this paper, we present an algorithm which automatically generates a geometry theorem from a starting point of a linear system of the type identified in Todd (Submitted to AMAI, 2022). Both statement and diagram of the new theorem are generated by the algorithm. Our implementation creates a simple text description of the new theorem and utilizes the Mathematica GeometricScene to form a diagram.</p></div>","PeriodicalId":7971,"journal":{"name":"Annals of Mathematics and Artificial Intelligence","volume":"91 6","pages":"779 - 795"},"PeriodicalIF":1.2000,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A program to create new geometry proof problems\",\"authors\":\"Philip Todd, Danny Aley\",\"doi\":\"10.1007/s10472-023-09854-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In a previous paper Todd (Submitted to AMAI, 2022), linear systems corresponding to sets of angle bisector conditions are analyzed. In a system which is not full rank, one bisector condition can be derived from the others. In that paper, we describe methods for finding such rank deficient linear systems. The vector angle bisector relationship may be interpreted geometrically in a number of ways: as an angle bisector, as a reflection, as an isosceles triangle, or as a circle chord. A rank deficient linear system may be interpreted as a geometry theorem by mapping each vector angle bisector relationship onto one of these geometrical representations. In Todd (Submitted to AMAI, 2022) we illustrate the step from linear system to geometry theorem with a number of by-hand constructed examples. In this paper, we present an algorithm which automatically generates a geometry theorem from a starting point of a linear system of the type identified in Todd (Submitted to AMAI, 2022). Both statement and diagram of the new theorem are generated by the algorithm. Our implementation creates a simple text description of the new theorem and utilizes the Mathematica GeometricScene to form a diagram.</p></div>\",\"PeriodicalId\":7971,\"journal\":{\"name\":\"Annals of Mathematics and Artificial Intelligence\",\"volume\":\"91 6\",\"pages\":\"779 - 795\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2023-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annals of Mathematics and Artificial Intelligence\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10472-023-09854-1\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Mathematics and Artificial Intelligence","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s10472-023-09854-1","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
In a previous paper Todd (Submitted to AMAI, 2022), linear systems corresponding to sets of angle bisector conditions are analyzed. In a system which is not full rank, one bisector condition can be derived from the others. In that paper, we describe methods for finding such rank deficient linear systems. The vector angle bisector relationship may be interpreted geometrically in a number of ways: as an angle bisector, as a reflection, as an isosceles triangle, or as a circle chord. A rank deficient linear system may be interpreted as a geometry theorem by mapping each vector angle bisector relationship onto one of these geometrical representations. In Todd (Submitted to AMAI, 2022) we illustrate the step from linear system to geometry theorem with a number of by-hand constructed examples. In this paper, we present an algorithm which automatically generates a geometry theorem from a starting point of a linear system of the type identified in Todd (Submitted to AMAI, 2022). Both statement and diagram of the new theorem are generated by the algorithm. Our implementation creates a simple text description of the new theorem and utilizes the Mathematica GeometricScene to form a diagram.
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.