The topology of boundaries

IF 4.6 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Artificial Intelligence Pub Date : 1996-01-01 DOI:10.1016/0004-3702(94)00051-4
Margaret M. Fleck
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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 Rn, 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 Rn 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.
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边界的拓扑结构
推理中使用的高级表示区分一组特殊的边界位置,在这些位置上函数值可能突然变化,相邻区域可能不连接。基于分割Rn的标准空间和时间模型不允许这些可能性,因为它们在边界处具有错误的拓扑结构。这种不匹配使得很难为高级推理算法开发正式的数学模型。本文展示了如何修改Rn模型,使其具有合适的拓扑结构。然后说明了新模型如何支持标准推理算法,为以前的困难情况提供简单的模型,并根据场景拓扑的变化或不变提出有趣的新分析。
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来源期刊
Artificial Intelligence
Artificial Intelligence 工程技术-计算机:人工智能
CiteScore
11.20
自引率
1.40%
发文量
118
审稿时长
8 months
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.
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