一种基于矩阵的MBR方向关系模型

在空间主方向关系推理的研究中,方向关系模型是其中一项至关重要的课题。介绍了区间代数模型、矩形代数模型和极小边界盒模型,提出了区间代数的矩阵表示方法,并给出了以矩阵表示的区间代数和方向关系矩阵之间的转换方法。     

基于间断区间的时间本体表示及应用

通过间断区间的时态理论扩展了OWL-Time,用在本体中表达单个事件带间断时区的情况。在本体中定义了间断区间概念以及间断区间的时态关系,并以物流领域运输事件的表示为例阐述了领域中基于间断区间的时间知识在本体中的表示方式。通过定义Jena中的原语、规则以及扩展对推理模型的操作构建了相应的推理机,对推理机进行实验检验,不仅验证了推理机运行的正确性,同时也保证了时间知识在本体和规则中表示的正确性,解决了带间断区间的时态知识在语义网中表示和推理的问题。     

基于强相关逻辑的不精确应急时态知识表示

在强相关逻辑基础上扩展不精确时态关系,以满足不精确应急时态知识表示与推理的需要。给出了粗糙集及强相关逻辑的相关概念;通过定义不精确时态关系扩展了强相关逻辑,形成了粗糙时态强相关逻辑,给出了可靠性和完备性证明;通过实际例子说明粗糙时态强相关逻辑的知识表示和应用。结果表明扩展后的粗糙时态强相关逻辑可以实现不精确时态知识的表示与推理。     

区间约束及其代数查询语言

提出了区间约束和基于区间约束的代数查询语言。区间约束与密序约束相经,增加了简单的加减运算,具有更强的描述能力,同时区间约束元组有简洁,唯一的规范区间表示,文中给出了计算区间约束的规范区间表示的算法,针对区间约束关系,定义了基本代数操作的语法及语义,研究了代数查询语言,并证明代数约束查询语言满足封闭性,最后讨论了区间约束的实现与应用。     

事件的持续时间的表示与推理

现实世界中事件的持续时间是难以精确测量的,其起始时刻及结束时刻经常是模糊的。本文用事件的持续函数的概念来表示事件的持续时间,并用有限的近似区间的概念来描述无限的持续函数,应用Heisenberg测不准原理,将Allen的区间代数网络的13种基本时态关系压缩为7种基本时态关系,并构造了新的基本时态关系的复合运算表。     

应急决策中基于时态知识的不确定性推理研究

针对应急决策中的不确定性,在传统区间代数方法的基础上,采用对区间时间断点模糊化处理并设定其取值范围的方法实现了应急领域不确定时态知识的表达,在此基础上,研究时态推理中的证据合成,通过时间区间集合,时态关系集合以及概率指派函数合成后的更新,给出了解决方案,结合应用算例进行分析。验证了该方法的有效性。     

区间集上的格蕴涵代数、FI-代数、MV-代数的研究

区间集是一个新的重要的研究方向,在近似推理、模糊控制等领域中有着广泛的应用。在区间集上,重新定义了区间蕴涵今,构造了格蕴涵代数,讨论了格蕴涵代数的一系列性质。同时在区间集上也重新定义了可换FI-代数和MV-代数,证明了格蕴涵代数、FI-代数和MV-代数3种不同的代数系统是等价的。     

基于间断区间的时态知识表示

一般,用逻辑形式表示时态信息的方法是命题附加一个时间点或时间区间。文［１］指出,时间区间表示单个事件带间断区间是困难的,不过,文［１］定义两个间断区间的时态关系为一个矩阵,其计算量相当之大以至该方法不实用二本文给出一个基于间断区间的时态知识表示模型,它将两个间断区间的时态关系分为２０种,其计算量与Ａｌｌｅｎ的区间演算属同一数量级。     

基于区间代数的工作流模式的建模研究

在业务流程建模阶段,从时态角度采分析业务流程,有助于清楚地描述工作流.在对工作流模式以及其中包含的时态语义进行了深入研究之后,根据区间代数的语法,将工作流模式和区间代数结合起来,提出了一种新的用于工作流模式的时间约束建模方法.它不仅从时态角度扩展了工作流建模,明确描述了工作流模式中和时序有关的时态约束和依赖关系,并且能使工作流控制模式和形式化验证工具结合,从而有利于进一步从时态角度研究业务流程建模.     

不确定时态信息表示的统一模型

时态信息表示和推理是人工智能研究中的一个重要课题,现有的模型大多只能表示确定时态信息,然而现实生活中很多事件的发生结束等时态信息都是不确定的。故提出了一个表示不确定时态信息的统一模型,可用于描述各种具有确定或不确定时态信息的事件。该模型首先定义各类时态对象(如时间点、时间区间)以及它们之间的关系,并给出时态对象间的传递关系表,利用该表能进行时态一致性约束满足问题的求解。最后,给出了两个不确定时态推理的例子,表明了该模型的实际应用意义。     

Modelling and solving temporal reasoning as propositional satisfiability

Representing and reasoning about time dependent information is a key research issue in many areas of computer science and artificial intelligence. One of the best known and widely used formalisms for representing interval-based qualitative temporal information is Allen's interval algebra (IA). The fundamental reasoning task in IA is to find a scenario that is consistent with the given information. This problem is in general NP-complete.In this paper, we investigate how an interval-based representation, or IA network, can be encoded into a propositional formula of Boolean variables and/or predicates in decidable theories. Our task is to discover whether satisfying such a formula can be more efficient than finding a consistent scenario for the original problem. There are two basic approaches to modelling an IA network: one represents the relations between intervals as variables and the other represents the end-points of each interval as variables. By combining these two approaches with three different Boolean satisfiability (SAT) encoding schemes, we produced six encoding schemes for converting IA to SAT. In addition, we also showed how IA networks can be formulated into satisfiability modulo theories (SMT) formulae based on the quantifier-free integer difference logic (QF-IDL). These encodings were empirically studied using randomly generated IA problems of sizes ranging from 20 to 100 nodes. A general conclusion we draw from these experimental results is that encoding IA into SAT produces better results than existing approaches. More specifically, we show that the new point-based 1-D support SAT encoding of IA produces consistently better results than the other alternatives considered. In comparison with the six different SAT encodings, the SMT encoding came fourth after the point-based and interval-based 1-D support schemes and the point-based direct scheme. Further, we observe that the phase transition region maps directly from the IA encoding to each SAT or SMT encoding, but, surprisingly, the location of the hard region varies according to the encoding scheme. Our results also show a fixed performance ranking order over the various encoding schemes.     

EvIA - Evidential Interval Algebra and Heuristic Backtrack-Free Algorithm

The Interval Algebra (IA) framework for temporal reasoning encodes indefinite knowledge in terms of disjunctions of relations. Many problems arising in practice can have evidences from past or from other external sources to indicate that some relations in a disjunction may be more probable than others. IA framework is inadequate to encode this information. The aim of the present study is two fold. First, to extend IA framework by associating numeric weights to the relations for capturing additional information and provide a reasoning methodology for the extended framework. Second, to apply the extended framework for developing a heuristic algorithm which finds a solution of the conventional IA network problem without backtrack. We make use of well-known evidential reasoning techniques to develop the new framework, Evidential Interval Algebra (EvIA). EvIA is an augmentation of interval algebra with evidential techniques. The constraint, constraint operators namely converse, composition and intersection, and path consistency algorithm of interval algebra are overlayed by evidential function and evidential operations to get enhanced expressiveness and efficient reasoning capability. The efficiency of the EvIA framework is demonstrated in the form of a heuristic which finds a solution of the interval algebra network without backtrack. Experimental results of the heuristic algorithm reveal that the algorithm is sound and for some specific types of the problems, the success of finding a solution is more than 90 percent. The results also show that the algorithm is efficient in terms of runtime when compared with a backtrack search algorithm.     

A possibility theory‐based approach to the handling of uncertain relations between temporal points

Uncertain relations between temporal points are represented by means of possibility distributions over the three basic relations precedes, equals, and follows. Operations for computing inverse relation, for composing relations, for combining relations coming from different sources and pertaining to the same temporal points, or for representing negative information are defined. An illustrative example of representation and reasoning with uncertain temporal relations is provided. This article shows how possibilistic temporal uncertainty can be handled in the setting of point algebra. Moreover, the article emphasizes the advantages of the possibilistic approach over a probabilistic approach previously proposed. This work does for the temporal point algebra what the authors previously did for the temporal interval algebra. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 157–179, 2007.     

时空推理中自动生成复合表的通用算法

时空推理是面向时间/空间问题的研究领域,在人工智能(如语义Web、机器人导航、自然语言处理、物理过程的定性模拟和常识推理等)和其他领域有着广泛的应用前景.复合推理在时空推理中具有重要作用,是约束满足问题等其他定性推理的基础.复合推理是由R(a,b)和R(b,c)决定R(a,c)的一种演绎推理.一般将关系复合结果放在复合表中备查.但目前复合表的建立需要逐个模型进行手工推导,少数模型给出了独立的复合表生成算法,没有适合多种时空关系模型、能自动生成复合表的通用算法.为此,提出了一种能自动生成复合表的通用算法.首先,给出了基于空间划分的通用时空表示模型.在此基础上,提出了基于场景检测的通用复合表生成算法.通过理论分析和对RCC、宽边界、区间代数等20余种典型时空模型的测试,证明了本算法对于所有以精确区域(或区间)为基础的确定、不确定时空模型均能正确快速地生成复合表.     

A STRENGTHENED ALGORITHM FOR TEMPORAL REASONING ABOUT PLANS

Allen's interval algebra has been shown to be useful for representing plans. We present a strengthened algorithm for temporal reasoning about plans, which improves on straightforward applications of the existing reasoning algorithms for the algebra. This is made possible by viewing plans as both temporal networks and hierarchical structures. The temporal network view allows us to check for inconsistencies as well as propagate the effects of new temporal constraints, whereas the hierarchical view helps us to get the strengthened results by taking into account the dependency relationships between actions.
We further apply our algorithm to the process of plan recognition through the analysis of natural language input. We show that such an application has two useful effects: the temporal relations derived from the natural language input can be used as constraints to reduce the number of candidate plans, and the derived constraints can be made more specific by combining them with the prestored constraints in the plans being recognized.     

Expressing Time Intervals and Repetition Within a Formalization of Calendars

We investigate a formal representation of time units , calendars , and time unit instances as restricted temporal entities for reasoning about repeated events. We generalize Allen's interval relations to a class level, and based on interval classes we define time units. We examine characteristics of time units, and provide a categorization of the hierarchical relations among them. Hence we define an abstract hierarchical unit structure (a calendar structure ) that expresses specific relations and properties among the units that compose it. Specific objects in the time line are represented based on this formalism, including nonconvex intervals corresponding to repeated events. A goal of this research is to be able to represent and reason efficiently about repetition in time.     

On the complemented disk algebra

The importance of relational methods in temporal and spatial reasoning has been widely recognised in the last two decades. A quite large part of contemporary spatial reasoning is concerned with the research of relation algebras generated by the “part of” and “connection” relations in various domains. This paper is devoted to the study of one particular relation algebra appeared in the literature, viz. the complemented disk algebra. This algebra was first described by Düntsch [I. Düntsch, A tutorial on relation algebras and their application in spatial reasoning, Given at COSIT, August 1999, Available from: <http://www.cosc.brocku.ca/~duentsch/papers/relspat.html>] and then, Li et al. [Y. Li, S. Li, M. Ying, Relational reasoning in the Region Connection Calculus, Preprint, 2003, Available from: http://arxiv.org/abs/cs/0505041] showed that closed disks and their complements provides a representation. This set of regions is rather restrictive and, thus, of limited practical values. This paper will provide a general method for generating representations of this algebra in the framework of Region Connection Calculus. In particular, connected regions bounded by Jordan curves and their complements is also such a representation.