{"title":"The topology of boundaries","authors":"Margaret M. Fleck","doi":"10.1016/0004-3702(94)00051-4","DOIUrl":null,"url":null,"abstract":"<div><div>High-level representations used in reasoning distinguish a special set of boundary locations, at which function values can change abruptly and across which adjacent regions may not be connected. Standard models of space and time, based on segmenting <span><math><mtext>R</mtext></math></span><sup><em>n</em></sup>, do not allow these possibilities because they have the wrong topological structure at boundaries. This mismatch has made it difficult to develop formal mathematical models for high-level reasoning algorithms. This paper shows how to modify an <span><math><mtext>R</mtext></math></span><sup><em>n</em></sup> model so as to have an appropriate topological structure. It then illustrates how the new models support standard reasoning algorithms, provide simple models for previously difficult situations, and suggest interesting new analyses based on change or non-change in scene topology.</div></div>","PeriodicalId":8434,"journal":{"name":"Artificial Intelligence","volume":"80 1","pages":"Pages 1-27"},"PeriodicalIF":4.6000,"publicationDate":"1996-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Intelligence","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/0004370294000514","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
High-level representations used in reasoning distinguish a special set of boundary locations, at which function values can change abruptly and across which adjacent regions may not be connected. Standard models of space and time, based on segmenting n, do not allow these possibilities because they have the wrong topological structure at boundaries. This mismatch has made it difficult to develop formal mathematical models for high-level reasoning algorithms. This paper shows how to modify an n model so as to have an appropriate topological structure. It then illustrates how the new models support standard reasoning algorithms, provide simple models for previously difficult situations, and suggest interesting new analyses based on change or non-change in scene topology.
期刊介绍:
The Journal of Artificial Intelligence (AIJ) welcomes papers covering a broad spectrum of AI topics, including cognition, automated reasoning, computer vision, machine learning, and more. Papers should demonstrate advancements in AI and propose innovative approaches to AI problems. Additionally, the journal accepts papers describing AI applications, focusing on how new methods enhance performance rather than reiterating conventional approaches. In addition to regular papers, AIJ also accepts Research Notes, Research Field Reviews, Position Papers, Book Reviews, and summary papers on AI challenges and competitions.