结合方向关系和拓扑关系的约束满足推理

结合定性空间推理中的区域连接演算（RCC）和基于区域的主方向关系模型,应用拓扑和方向关系上的复合表,将方向关系和拓扑关系的推理看作约束满足问题（CSP）,给出了结合RCC8和主方向关系的约束满足问题推理算法,该算法可结合拓扑关系和方向关系进行推理。     

RCC5与主方位关系结合的定性空间推理

解决实际问题需要将多方面空间信息结合进行推理,仅考虑单方面空间信息是不够的.多方面空间信息结合推理已成为定性空间推理的一个研究热点.现有拓扑与方位结合推理工作主要集中在与基于最小外包矩形或单片方位模型的结合.方位信息描述是近似的,不适于精确推理;因此分别采用主方位模型和RCC5描述方位、拓扑信息.根据定义给出基本RCC5和主方位关系间的相互依赖及异质复合表;讨论了其上约束满足问题,得到一个路径相容算法,并分析了推理复性问题.     

基于MBR的拓扑、方位、尺寸结合的定性空间推理

解决实际问题需将多方面空间关系结合进行推理,多方面空间关系结合推理已成为定性空间推理的研究热点;已有工作主要集中在两方面空间关系结合,缺少两方面以上空间关系结合工作.为解决上述问题,通过最小外包矩形近似表示区域对象,利用其在坐标轴上投影间的关系表示相应空间关系;提出扩展矩形关系模型,实现拓扑、方位和尺寸关系的统一表示和推理;给出RCC8、主方位及尺寸关系转换成扩展矩形关系的转换算法;讨论其上关系取反和复合,指出其复合是基于相容性而非存在性;证明(强预)凸扩展矩形关系约束网是可处理的.     

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。     

混合维拓扑和尺寸关系的定性空间推理

定性空间推理(QSR)研究空间关系,多数工作集中在单维空间关系,但在地理信息系统(GIS)中多维对象很常见.混合维对象空间关系是指点、线和区域3类对象出现在同一场景的情况,该类问题对定性空间推理研究有着重要的理论意义和应用价值.但这方面的研究工作还比较少.在已有的混合维区域连接演算的基础上进行完善,提出了MRCC5混合维拓扑模型,并研究了其上约束满足推理问题的复杂度.对定性尺寸关系进行了混合维扩展.给出了MDS模型,进而研究了其推理问题.在以上工作基础上.提出了RCCA和MDS的结合模型,给出并分析了结合模型的推理算法.将定性空间推理相关研究推广到混合维领域,深入研究了混合维拓扑关系推理,提出了混合维尺寸以及混合维拓扑尺寸结合模型.     

集成多方面信息的定性空间推理及应用

以往的定性空间或时空推理工作多数面向单一时空方面,这不符合实际应用需要.提出了集成拓扑、尺寸和时间3方面信息的定性表示和推理技术,并应用到时空GIS中.给出了面向GIS的拓扑、尺寸和时间的表示方法,并研究了它们之间的依赖性.提出了集成这3方面信息的约束满足问题求解算法TriRSAT.在时空GIS中,把定性时空表示用于约束关系库,把TriRSAT算法用于时空数据一致性检查和时空查询.应用结果显示,该理论和方法能有效地集成处理多方面时空信息,在时空数据库、机器人导航等领域有着广泛的应用前景.     

约束满足问题求解途径之比较与分析

本文从逻辑,自动机理论,代数方法,连接主义框架和遗传算法的角度深入地探讨了ＣＳＰ问题的不同表示框架和求解风范,详细分析和讨论了不同表示和求解方法的特点以及它们之间的内在联系和可能的结合。     

几何约束满足问题的图重构策略

通过对图缩并算法的介绍和分析 ,以约束网络图的形式对几何约束系统中的约束关系进行映射表达 ,提出了一种基于自由度分析的图重构推理策略 ,实现了问题的最大分解 ,大大降低了问题的复杂程度和系统求解的规模 ,使得相当一部分具有高耦合性的问题最终可以用解析方法求解。     

基于结合空间拓扑和方向关系信息的空间推理

结合了定性空间推理中著名的区域连接演算（region connection calculus,RCC）和基于区域的方向关系演算（cardinal direction calculus,CDC）,并且给出两个演算在两个方向上的交互表,即RCC8-To-CDC和CDC-To-RCC8．给出了结合RCC8和CDC知识的约束满足问题的路径一致算法（path consistency algorithm）（该算法是对Allen著名的路径一致算法的修改）,并且采用两个队列实现了该算法,采用这种结构可以实现并行计算．在该算法中,基于以上两个交互表的交互操作被嵌入到算法里面来保证整个约束满足问题的一致性．算法的计算复杂性证明是多项式的,     

非二元约束满足问题求解

在约束满足问题(CSP)的研究中,大部分工作集中在二元约束,但处理实际问题时,常常会遇到非二元约束的情况．该文在概要地讨论了两类求解非二元约束问题方法的基础上,研究了一种将约束传播技术和一般弧相容回溯算法相结合的非二元约束求解方法,并在设计开发的约束求解工具“明月SOLVER1.0”中实现了该方法,以典型例子给出了实现系统的运行结果．     

Multi-granularity and metric spatial reasoning

Composition reasoning is a basic reasoning task in qualitative spatial reasoning (QSR). It is an important qualitative method for robot navigation, node localization in wireless sensor networks and other fields. The previous composition reasoning works dedicated in single granularity framework. Multi-granularity spatial relation is not rare in real world, and some qualitative spatial relation models are multi-granularity models, such as RCC, STAR_m, CDC_m and OPRA_m. Although multi-granularity composition reasoning is very useful in many applications, it has not been systematically studied before. A special case of multi-granularity composition reasoning, referred to as metric spatial reasoning, is also discussed here. The general frameworks and basic theories for multi-granularity and metric spatial reasoning are put forward here. Furthermore, we redefine the spatial relation models for distance, topology and direction under the proposed multi-granularity and metric frameworks. We add metric representation for the OPRA_m. The multi-granularity and metric reasoning tasks are studied for these four models for the first time. Finally we perform some experiments on OPRA_m with encouraging results to verify our theories. Multi-granularity and metric spatial reasoning tasks are new problems in QSR and quite different from the previous works. Our works can be potentially applied in robot navigation, wireless sensor networks and other applications.     

Qualitative reasoning with directional relations

Qualitative spatial reasoning (QSR) pursues a symbolic approach to reasoning about a spatial domain. Qualitative calculi are defined to capture domain properties in relation operations, granting a relation algebraic approach to reasoning. QSR has two primary goals: providing a symbolic model for human common-sense level of reasoning and providing efficient means for reasoning. In this paper, we dismantle the hope for efficient reasoning about directional information in infinite spatial domains by showing that it is inherently hard to decide consistency of a set of constraints that represents positions in the plane by specifying directions from reference objects. We assume that these reference objects are not fixed but only constrained through directional relations themselves. Known QSR reasoning methods fail to handle this information.     

求解约束网络图的逆向推理方法

本文研究了几何约束网络的求解问题。首先,介绍了常用的几何推理方法,指出了存在的问题。然后,提出了求解约束网络图的一种新方法——逆向推理方法,阐明了基本思想,并给出了应用实例。逆向推理方法继承了几何推理方法的优点,克服了其不足。     

Symmetry Definitions for Constraint Satisfaction Problems

We review the many different definitions of symmetry for constraint satisfaction problems (CSPs) that have appeared in the literature, and show that a symmetry can be defined in two fundamentally different ways: as an operation preserving the solutions of a CSP instance, or else as an operation preserving the constraints. We refer to these as solution symmetries and constraint symmetries. We define a constraint symmetry more precisely as an automorphism of a hypergraph associated with a CSP instance, the microstructure complement. We show that the solution symmetries of a CSP instance can also be obtained as the automorphisms of a related hypergraph, the k-ary nogood hypergraph and give examples to show that some instances have many more solution symmetries than constraint symmetries. Finally, we discuss the practical implications of these different notions of symmetry.     

空间关系推理的研究方法

空间关系推理在地理信息系统、空间数据挖掘、模式识别、机器人学、专家系统、图形与图像处理和自然语言理解等方面具有广泛的应用。近年来,国内外专家对空间关系推理进行了大量的研究,取得了一系列的研究成果。介绍了国内外在空间关系推理方面的研究方法和研究成果,并且进行了比较和分析,概括了已有方法的特点和不足,讨论了该领域未来的研究重点和难点。     

近似空间关系代数ASRA及应用

粗定位模型是一种基于粗集的近似区域表示模型 ,基于定性空间推理理论对其进行了代数形式化 .通过空间关系矩阵和 2 4 9种基本空间关系构造了近似空间关系代数 ASRA;讨论了 ASRA的公理和基本性质 ,研究了ASRA和 RCC5关系映射中存在的不确定性 ;把 ASRA应用于 GIS,提出了基于 ASRA的空间关系判定算法ASRA- RCC.与同类算法相比 ,ASRA- RCC能够同时支持确定和近似区域 ,并且具有较高的效率     

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     

Spatial Reasoning About Points in a Multidimensional Setting

For n 1, we consider the possible relations between two points of the Euclidean space of dimension n. We define the n-point algebra on the pattern of the point algebra and the cardinal algebra. Generalizing the concept of convexity just as the one of preconvexity, we prove that the consistency problem of convex n-point networks is polynomial for n 1, whereas the consistency problem of preconvex n-point networks is NP-complete for n 3. We characterize a subset of the set of all preconvex relations: the set of all strongly preconvex relations, which contains the set of all convex relations. We demonstrate that the consistency problem of strongly preconvex n-point networks can be decided in polynomial time by means of the weak path-consistency method for all n 1. For n = 3 the set of all strongly preconvex relations is a maximal tractable subclass of the set of all n-point relations. Finally, we prove that the concept of strong preconvexity corresponds to the one of ORD-Horn representability.     

There are no pure relational width 2 constraint satisfaction problems

In this note, we show that every constraint satisfaction problem that has relational width 2 has also relational width 1. This is achieved by means of an obstruction-like characterization of relational width which we believe to be of independent interest.