定性空间表示与定性空间的研究与发展

1 引言空间推理是指利用空间理论和人工智能技术对空间对象建模、描述和表示,并据此对空间对象间的空间关系进行的定性或定量的分析和处理过程。在描述和推断空间对象间的空间关系时,要获得精确、定量的数据通常是不可能的或不必要的,在这种情况下,可能要用到关于空间关系的定性空间推理。定性空间推理是一个     

空间方向关系定性推理技术研究进展

空间方向关系是空间认知中的一个基本概念，在空间数据库、人工智能、机器人等领域发挥着极其重要的作用。随着对空间方向关系研究的不断深入，空间方向关系定性推理受到了广泛关注，逐渐成为研究的热点。为了更进一步地介绍和挖掘空间方向关系推理技术的研究现状，首先，针对现有的推理模型进行详细梳理和总结，对各类模型进行比较和分析，指出了各种模型的特性及适用范围；其次，从二维、三维及不确定性空间对象方向关系的复合、反关系推理、一致性检验以及结合多种空间信息的组合推理等几个方面，对空间方向关系推理相关工作进行了系统性的阐述和分析；最后，分析了目前所面临的挑战，并对其未来发展趋势进行了展望。     

时空推理研究进展

与时态和空间有关的推理问题是人工智能研究中重要的组成部分,在地理信息系统、时空数据库、CAD/CAM等领域有着重要应用.从本体、表示模型和推理方法3个方面分别介绍了时态推理和空间推理的发展,并在此基础上综述了时空结合推理的研究进展.讨论了目前时空推理领域存在的问题,并指出了今后的发展方向.     

方位关系约束满足问题的推理求解

约束满足问题（Constraint Satisfaction Problems CSP）是人工智能的一个研究领域,诸如空间查找、规划等问题都可转化为约束满足问题。方位关系是空间关系的重要组成部分,用以确定空间对象间的一种顺序。本文研究了空间方位关系模型,给出了方位关系约束的一般表示形式。在此基础上,利用组合表推理给出了方位关系约束满足问题的一个推理求解算法,该算法的时间复杂度为O（n^2）。     

结合度量空间和时间的逻辑

与时态和空间有关的推理问题是人工智能研究中重要的组成部分，近年来时空逻辑的研究受到相关领域研究者的极大重视。以多维逻辑为框架表示时空知识，提出了一组将度量空间逻辑和时态逻辑相结合的逻辑模型PTL-MS、PTL-MS1、PTL-MS2，表示和推理随时间变化的距离关系，看成是时态逻辑和度量逻辑的迪卡尔乘积，给出了语义和语法，研究了它们的表达能力，用于时空约束满足问题、时空知识库以及移动对象数据库(MOD)等。     

一种基于主特征的几何空间模糊推理方法

在几何空间中关于几何体之间不确定关系的推理是空间推理技术的主要研究方向,首先,提出了空间几何体的特征与主特征的概念,并证明了几何体特征之间的关系与几何体之间的基本关系的等价性;其次,引入了相邻、平行、从属、同线、线性等空间关系来描述空间几何体主特征之间的关系,并且将这几种空间关系通过隶属度函数模糊化;最后,基于主特征之间的空间关系,提出了一种进行空间模糊推理的方法,并给出了相应的应用实例,表明了所提出的方法是有效的、可行的。     

知识推理在GIS中的应用

传统的GIS平台具有完成数据采集、管理、存储、处理和一定的空间分析功能,但其空间分析推理和决策能力较弱。将人工智能中有关推理、分析的技术引入到GIS中,使GIS能够具备一定的空间推理分析能力,将弥补GIS对于决策支持方面的不足,发挥其效能,使之能够解决更为复杂的问题。并在最后设计了一个“自助驾车游北京”的智能咨询模型。     

异构几何集合对象拓扑关系的描述

拓扑关系是一种非常重要的空间关系，在地理信息系统(GIS)中，被广泛地应用于空间查询、空间分析和空间推理。目前，已经提出了多种模型来对空间对象间的拓扑关系进行描述。在GIS中，空间对象包括单一(简单或复杂)的空间对象、同构的几何集合对象和异构的几何集合对象。目前国际上     

定性空间推理的研究与进展

定性空间推理是人工智能学科处理常识性空间知识的一种方法[l],其推理任务包括图:推导知识库中的隐含知识;针对给定的部分知识或特定的上下文回答询问;维护一致性;获取新知识特别是认知图;定性场景描述的可视化。     

存储于关系数据库的知识库的语义推理方法

语义推理的功能使得知识库更具人工智能,具有实用意义。文章根据语义模型的特点,构建了基于关系数据库的知识库语义存储体系,该存储体系的模式空间和实例空间相分离,降低了结构和数据的耦合性,使语义的存储范围更具完整性、语义的推理效果更具智能性。面向该存储体系的语义推理方法实现了相关语义(专家知识)的推理和相似语义(词汇)的推理,同时,该方法也考虑到了推理范围的可控能力和推理结果的语义还原能力。分析表明,该方法能应用于实际,但仍存在一些可改进之处。     

GIS中拓扑关系及空间推理研究

通过研究分析GIS中的核心问题——空间拓扑关系,将空间推理引入拓扑关系的研究中,并在拓扑推理的基础上,提出加入方向关系的推理机制,最后给出了推理的模型。     

基于粒度层次的方位关系推理

方位关系推理是空间推理的一个重要方面。本文主要研究的是方位关系推理的问题之一——基于层次的方位关系表示与推理。文中首先从区域间的覆盖关系出发，提出了基于空间粒度的层次划分方法；然后，从“点对象”和“矩形对象”两个方面研究了基于粒度层次的方位关系表示与推理方法，并给出了相应的推理算法。文中的推理实例验证了粒度划分与推理方法的可行性。     

Spatial inference with geometric proportional analogies

We describe an instance-based reasoning solution to a variety of spatial reasoning problems. The solution centers on identifying an isomorphic mapping between labelled graphs that represent some problem data and a known solution instance. We describe a number of spatial reasoning problems that are solved by generating non-deductive inferences, integrating topology with area (and other) features. We report the accuracy of our algorithm on different categories of spatial reasoning tasks from the domain of Geographical Information Science. The generality of our approach is illustrated by also solving geometric proportional (IQ-test type) analogy problems.     

Perceptual and signal detection factors in radiography

Diagnostic imaging systems (e.g. X-rays and ultrasound) play an important role in medicine. Owing to increasing workloads now carried by clinical radiologists, the interpretation of medical images is increasingly being passed to radiographers. This is especially so in those areas of diagnoses where examinations are performed on large numbers of patients but when the frequency of the disorder is very low (e.g. mass mammography screening). This study explored the accuracy of the radiographic interpretation of pulmonary nodules by clinical radiologists and student radiographers, and their correlations with tests of field-dependency, visual search and spatial reasoning. Overall performance in lung nodule detection gave a mean ROC (Az)=0.851 for student radiographers, while radiologists achieved 0.871. No correlation was found between diagnostic performance and either field-dependency or visual search. A significant negative correlation was found between diagnostic performance and spatial reasoning (p < 0.05).     

Using sign algebra for qualitative spatial reasoning about the configuration of mechanisms

This paper presents a novel approach to qualitative spatial reasoning about the spatial configuration of mechanisms that could be applied in the earlier phases of mechanism design. The basic idea in this approach is to predict all possible spatial configurations of a mechanism using sign algebra. This paper addresses spatial configuration problems of direction, position, and orientation of mechanisms. Spatial configuration matrices are introduced to describe and manipulate the spatial information of primitive mechanisms. Using these matrices, the overall spatial configurations of a complicated mechanism are constructed and then they are expressed by spatial configuration state matrices. These matrices are composed based on sign algebra and used to reason about all possible spatial solutions of a mechanism. The qualitative spatial reasoning proposed in this paper could provide useful prior information on the spatial configuration of mechanisms earlier in the conceptual design of mechanisms. The proposed approach is illustrated with a design example.     

Spatial reasoning in a fuzzy region connection calculus

Although the region connection calculus (RCC) offers an appealing framework for modelling topological relations, its application in real-world scenarios is hampered when spatial phenomena are affected by vagueness. To cope with this, we present a generalization of the RCC based on fuzzy set theory, and discuss how reasoning tasks such as satisfiability and entailment checking can be cast into linear programming problems. We furthermore reveal that reasoning in our fuzzy RCC is NP-complete, thus preserving the computational complexity of reasoning in the RCC, and we identify an important tractable subfragment. Moreover, we show how reasoning tasks in our fuzzy RCC can also be reduced to reasoning tasks in the original RCC. While this link with the RCC could be exploited in practical reasoning algorithms, we mainly focus on the theoretical consequences. In particular, using this link we establish a close relationship with the Egg-Yolk calculus, and we demonstrate that satisfiable knowledge bases can be realized by fuzzy regions in any dimension.     

Spatial persistence

We examine the spatial version of the persistence problem. In temporal reasoning, this is the problem of determining whether or not the validity of a fact at some point in time persists until another point in time, given that certain events or processes may happen in between. We show that its analog does intuitively exist in spatial reasoning, and review under the aspect of transferability to space different approaches for achieving persistence in temporal reasoning. Finally, we present reasoning with generalized spatial Allen relations as an instance of reasoning under the assumption of spatial persistence.This author has partially been supported under grant numbers A18/XXXXX/62090/3414014 and A18/XXXXX/62090/F3414025 by the University of Auckland Research Fund.     

结合拓扑和方位的定性空间推理方法*

空间区域的拓扑关系和方位关系是空间推理的重要研究内容,以往的工作集中在单一的空间方面, 这不能满足实际应用领域的需要.基于主方位模型给出了主方位关系的形式化定义,考虑到拓扑与方位间的相互依赖关系,提出了结合拓扑和方位的定性表示与推理算法,能够处理多方面空间信息,在空间数据库和机器人导航等领域具有实际应用价值.     

Spatial reasoning and similarity retrieval for image database systems based on RS-strings

In this paper, we propose a rotation-invariant spatial knowledge representation called RS-string. Then we present the string generation algorithm to automatically generate RS-strings for segmented pictures. We also propose the spatial reasoning and similarity retrieval algorithms based on RS-strings. The similarity retrieval algorithm is much more flexible than all previous 2D string representations because our approach can consider every possible view of a query picture. Thus the system does not require the user to provide a query picture which must have the same orientation as that of a database picture. Finally, we provide several examples to demonstrate the capabilities of spatial reasoning and similarity retrieval based on the RS-string representation.