A uniform formal description of data base management systems

This paper attempts for the first time to formulate the majority of data base functions in an homogeneous and formal manner, in contrast to other methods which treat little more than the data manipulation functions. The main task of a data base management system is to execute certain uniform operations on a given set of data resources. Most problems of data base management systems can be deducted from this main task, in that a framework is provided both for investigating existing systems or designing new ones.     

A probabilistic plan recognition algorithm based on plan tree grammars

We present the PHATT algorithm for plan recognition. Unlike previous approaches to plan recognition, PHATT is based on a model of plan execution. We show that this clarifies several difficult issues in plan recognition including the execution of multiple interleaved root goals, partially ordered plans, and failing to observe actions. We present the PHATT algorithm's theoretical basis, and an implementation based on tree structures. We also investigate the algorithm's complexity, both analytically and empirically. Finally, we present PHATT's integrated constraint reasoning for parametrized actions and temporal constraints.     

一种服务网络拓扑结构的形式化描述方法

本论文提出了一种服务网络拓扑结构的形式化描述方法,该方法定义服务、业务和ICT组件之间的关系,并将形式化地定义ICT路径的描述。通过该方法能够有效地实现服务网络的可用性及服务风险的量化。     

数字隐写模型及形式化描述

为了使数字隐写模型研究与隐写技术研究同步发展,从通用到具体,依次提出3个数字隐写模型,并对各模型进行形式化描述,总结梳理隐写算法的本质原理,以指导隐写技术的进一步发展。首先,针对已有模型无法描述新兴隐写算法的问题,提出一个通用数字隐写模型,以描述当前所有隐写算法;其次,鉴于载体修改式的隐写算法在隐写术研究中的重要地位,提出基于载体修改的加性噪声隐写模型;然后,针对当前主流的图像自适应隐写算法,提出具体的最小化失真的数字图像自适应隐写模型。选取4个典型的隐写算法实例,采用所提隐写模型进行对应描述,以验证所提模型的有效性。     

RSL在协议形式化描述中的应用研究

将RSL引入协议工程,探讨了对协议进行形式化描述的一条新途径。为RSL扩充了时间描述机制,讨论了基于两类基本模型（状态模型和进程模型）的协议描述方法及一般描述步骤。以示例方式给出了RIP路由简化算法的RSL形式化描述。与其他方法相比,扩充后的RSL描述能力强,描述手段灵活,能更有效地支持验证、测试等后续阶段的工作。     

A formal approach to the design of feature-based multi-sensor recognition systems

This paper shows an example of developing a fusion system in a formal framework, i.e., through the use of formal operators in the development process. Two main concepts of formal methods are theories and models. In our approach, the development of a fusion system consists of operations on theories and models. We show, on a simple example, how theories and models are combined in the process of designing a fusion system. We also compare the performance of a system developed according to our approach with a more traditional system.     

空间方向关系形式化描述研究进展

空间方向关系的表示与建模作为空间方向关系领域的一个基础性问题,近年来逐渐成为地理信息系统、空间数据库和人工智能等领域研究的热点和难点并取得了一系列研究成果。从二维空间精确对象方向关系模型、三维空间对象方向关系模型、模糊空间方向关系模型等几个方面全面地综述了空间方向关系形式化描述的研究进展, 并对各种模型进行了对比与分析,指出了它们的优势与不足。最后明确指出三维空间方向关系和模糊空间方向关系建模是未来工作的重点,特别是三维模糊对象方向关系的研究是未来空间方向关系研究的重中之重,并指出进一步研究中几个迫切需要解决的关键问题。     

基于形式概念分析的粗糙描述逻辑研究

以往的粗糙描述逻辑(RDL)都是基于传统的粗糙集理论。实际上,经常会出现用形式概念表示一个概念的情况,此时一个自然的问题就是如何处理可能出现的不确定概念。把形式概念分析与粗糙集理论联系起来做为基础,给出可定义概念和不可定义概念的定义,并给出不可定义概念的上近似和下近似,这里的近似定义虽然不同于传统的粗糙近似算子形式,但是有很好的实用性。基于新的上下近似定义,把一组近似算子引入到描述逻辑的结构中,形成一种新的粗糙描述逻辑。给出了相应的语法和语义,最后还给出了扩展的Tableau算法,可以用来解决相应的推理问题。     

基于Pi-演算的Web服务形式化描述模型*

当前对Web服务进行形式化描述的方法多是基于对某个具体Web服务组合规范的抽象,无法兼顾基于全局和局部的设计方法,并且无法描述Web服务组合的体系结构的动态性。本文在对现有的Web服务形式化描述方法进行回顾和总结的基础上,基于Pi-演算建立了Web服务形式化描述模型,将BPEL4WS规范和WS-CDL规范的重要行为在模型中做了映射。最后通过例子说明,基于局部和全局的设计方法在本文提出的模型中的映射是一致的。本文提出的描述模型直接用来进行Web服务组合的设计时,可以更好的描述动态的体系结构。     

改进高维数据相似度的目标意图识别方法

对于实际战场中目标属性要素呈现出的多样化,传统目标意图识别方法不能够较全面地建立属性之间的相似度模型.为了更好地阐述实际战场的复杂情况,提高目标意图识别的准确度,提出了一种利用改进的空间相似度与属性相似度融合的高维数据相似度模型,以全面地计算目标各种属性状态对态势意图的支持程度,再利用得到的高维数据相似度通过D-S证据理论对目标进行序贯识别.仿真实验表明:该方法具有有效性以及能够提高目标意图识别的准确度,为解决目标战术意图识别提供了新的方法.     

A meta-rule approach to flexible plan recognition in dialogue

Although a number of researchers have demonstrated that reasoning on a model of the user's plans and goals is helpful in language understanding and response generation, current models of plan inference cannot handle naturally occurring dialogue. This paper argues that model building from less than ideal dialogues has a great deal in common with processing ill-formed input. It defines well-formedness constraints for information-seeking dialogues and contends that strategies for interpreting ill-formed input can be applied to the problem of modeling the user's plan during an ill-formed dialogue. It presents a meta-rule approach for hypothesizing the cause of dialogue ill-formedness, and describes meta-rules for relaxing the plan inference process and enabling the consideration of alternative hypotheses. The advantages of this approach are that it provides a unified framework for handling both well-formed and ill-formed dialogue, avoids unnatural interpretations when the dialogue is proceeding smoothly, and facilitates a nonmonotonic plan recognition system.Rhonda Eller is a Ph.D. candidate in Computer Science at the University of Delaware. She received her B.S. in Computer Science from Millersville University of Pennsylvania in 1987, and her M.S. degree in the same field from the University of Delaware. Her primary interests lie in the areas of natural language processing, plan recognition, and user modelling. This paper summarizes the current state of her thesis work on repair of an incorrectly inferred plan for a user.Sandra Carberry is an associate professor of computer science at the University of Delaware. Her research interests include discourse understanding, user modeling, planning and plan recognition, and intelligent natural language interfaces. This paper describes work that is part of an ongoing research project to develop a robust model of plan recognition.     

概率规划识别的研究*

概率规划识别由于其自身的实用性,已经成为人们关注的热点。因此,越来越多的学者致力于该领域的研究,至今已研发出多款高效优质的概率规划识别器,都取得了良好的效果。为了使广大学者对概率规划识别有一个较为全面的了解,就概率规划识别的发展、求解方法及其应用作了介绍。     

Controlling inference in plan recognition

An algorithm based on an assessment of the completeness of an explanation can be used to control inference in a plan recognition system: If the explanation is complete, inference is stopped. If the explanation is incomplete, inference is continued. If it cannot be determined whether the explanation is complete, then the system weighs the strength of its interest in continuing the analysis against the estimated cost of doing so. This algorithm places existing heuristic approaches to the control of inference in plan recognition into a unified framework. The algorithm rests on the principle that the decision to continue processing should be based primarily on the explanation chain itself, not on external factors. Only when an analysis of the explanation chain proves inconclusive should outside factors weigh heavily in the decision. Furthermore, a decision to discontinue chaining should never be final; other components of the system should have the opportunity to request that an explanation chain be extended. An implementation of the algorithm, called PAGAN, demonstrates the usefulness of this approach.Dr. James Mayfield is Assistant Professor of Computer Science at the University of Maryland at Baltimore County. He completed his Ph.D. in 1989 at the University of California at Berkeley, under the direction of Dr. Robert Wilensky. His paper reflects his ongoing interest in plan recognition. Dr. Mayfield's other research interests include the detection and resolution of ambiguity, and the automatic conversion of linear text to hypertext.     

Student modelling using plan recognition

Abstract

We present a student modelling approach based on plan recognition methods. In some domains, like theorem proving, the student's activity can be seen as consisting of the formation of plans (the proofs) and the execution of actions (the proof steps). Starting from the student's inputs and the problem's search space, the method infers the most plausible plan according to a criterion of coherence. Recognising the student's plan can help predict his next actions and provide him with well-adapted assistance. This modelling technique is applied in an intelligent tutoring system (ITS) which coaches a student during geometry problem-solving. We describe the architecture of the system: the expert, a set of geometry rules together with a theorem prover which can solve problems in different ways and recognise the student's errors; the interface; and the pedagogical module. Finally, we describe the implemented system and its evaluation.     

Knowledge-driven description synthesis for floor plan interpretation

International Journal on Document Analysis and Recognition (IJDAR) - Image captioning is a widely known problem in the area of AI. Caption generation from floor plan images has applications in...     

规划识别的研究及其应用

规划识别是人工智能研究领域的一个重要分支.由于近年来的广泛应用,规划识别的重要性被越来越多的学者所认同.对规划识别领域的大量文献进行广泛而深入研究,从整体上阐述了规划识别问题,较为全面地介绍了规划识别的发展历程、分类、方法以及应用,并着重介绍了规划识别目前较为流行的技术方法和热门应用,公开了几个未解决的问题.