对象的类比推理研究

本文首先提出对象与对象抽象、规则序与规则映射的理论,为对象的类比推理奠定了一定的基础,在此基础上,建造了对象类比推理模型ＯＡＭ．     

基于模板技术的汽车多体动力学建模研究

针对当前汽车动力学仿真软件建模复杂度高、模型结构不易理解、模板开放性不高等缺点,提出开放的模板化建模技术.将汽车动力学模型分解为相对独立的子系统并抽象为基本模板,采用“基本模板—结构模板—模板实例化”的架构,用XML描述模板,从而实现模板的开放性,构建汽车动力学模型的树状层级模板库和实例库,结合基于实例推理的方法生成模型.在此基础上开发了汽车整车建模软件,并以某重型汽车起重机为例说明了该技术的应用.     

Extended object model for product configuration design

This paper presents an extended object model for case-based reasoning (CBR) in product configuration design. In the extended object model, a few methods of knowledge expression are adopted, such as constraints, rules, objects, etc. On the basis of extended object model, case representation model for CBR is applied to product configuration design system. The product configuration knowledge can be represented by the extended object. The model can support all the processes of CBR in product configuration design, such as case representation, indexing, retrieving, and case revising. The presented model is an extension of the traditional object-oriented model by including the relationship class used to express the relation between the cases, constraints class used in the product configuration knowledge representation, index class used in case retrieving, and solution class used in case revising. Therefore, the product configuration knowledge used in the product configuration design can be represented by using this model. In the end, a metering pump product configuration design system is developed on the basis of the proposed product configuration model to support customized products.     

Case-Based Learning: Predictive Features in Indexing

Interest in psychological experimentation from the Artificial Intelligence community often takes the form of rigorous post-hoc evaluation of completed computer models. Through an example of our own collaborative research, we advocate a different view of how psychology and AI may be mutually relevant, and propose an integrated approach to the study of learning in humans and machines. We begin with the problem of learning appropriate indices for storing and retrieving information from memory. From a planning task perspective, the most useful indices may be those that predict potential problems and access relevant plans in memory, improving the planner's ability to predict and avoid planning failures. This predictive features hypothesis is then supported as a psychological claim, with results showing that such features offer an advantage in terms of the selectivity of reminding because they more distinctively characterize planning situations where differing plans are appropriate.We present a specific case-based model of plan execution, RUNNER, along with its indices for recognizing when to select particular plans—appropriateness conditions—and how these predictive indices serve to enhance learning. We then discuss how this predictive features claim as implemented in the RUNNER model is then tested in a second set of psychological studies. The results show that learning appropriateness conditions results in greater success in recognizing when a past plan is in fact relevant in current processing, and produces more reliable recall of the related information. This form of collaboration has resulted in a unique integration of computational and empirical efforts to create a model of case-based learning.     

A generic, object-oriented case-knowledge representation scheme, and its integration into a wider information management scenario

Abstract: A knowledge base management system (KBMS) realises a combination of techniques found in database management systems and knowledge-based systems. At the data model and knowledge representation level, many systems of this kind constitute a marriage of the relational data model and the rule-based reasoning. Experience has shown that either approach is restricted in the way it can express the demanding information and knowledge structures required for applications like decision support systems. Two new technologies offer an exciting new integrated approach to knowledge management. Object-oriented database management systems (OODBMS) provide an object model that supports powerful abstraction mechanisms to facilitate the modelling of highly structured information. Whereas case-based reasoning (CBR) systems are knowledge bases which organise their capabilities around a memory of past cases and the notion of similarity. Both types of system are built upon two fundamental concepts: 1) the retrieval of entities with potentially complex structure, called objects in the former, and cases in the latter type of system; 2) the organisation of those entities in collections with common characteristics. In an OODBMS such collections are termed extents, and in CBR they are usually called categories. In either system, the conceptual meta notion to represent both, objects as well as extents, and cases as well as categories, is the class.
Revolving around a Conceptual Case Class and extending a standard object model, this paper proposes a novel and general approach to represent case-knowledge and to build KBMSs. The work presented here is a spin-off of the design of an object query language within the ESPRIT project Lynx.     

Software modeling and analysis using a hierarchical object-oriented Petri net

Petri net is used widely to analyze and model various systems formally. Recently, many Petri nets mania devote their efforts to enhancing and extending the expressive power of Petri nets. One such effort is to extend Petri nets with object-oriented concepts. An object-oriented paradigm provides excellent concepts to model real-world problems. Object-oriented concepts allow us to build software systems easily, intuitively, and naturally. Although several high-level Petri nets with the concept of objects are suggested, these nets do not fully support the object-oriented concepts. In this paper, we propose a hierarchical object-oriented Petri net (HOONet). The formal syntax and semantics of HOONet are explained in detail. HOONet supports a wide range of object-oriented features including abstract, encapsulated and modularized objects, object interaction by message passing, inheritance, and ploymorphism. HOONet also supports a variety of modeling and analysis mechanisms such as incremental modeling of evolving systems, unfolding the HOONet to lower level Petri net, and incremental reachability analysis for HOONet models. We demonstrate the usefulness of HOONet by applying it to modeling and analysis with an example.     

基于案例推理的柔性工作流建模技术研究

针对工作流模型难以描述创建时的不确定因素的问题,研究了一种基于“柔性块”的柔性工作流建模技术。运行时,柔性块先以Ad hoc方式执行,运行历史数据积累到一定程度后,通过过程挖掘得到柔性块内部模型,并在以后执行时匹配应用场景,采用交互式基于案例的推理方法获得柔性块模型。实际应用表明该方法能复用建模知识,柔性块建模效率随着其执行次数增多而提高,工作流模型具有较高的柔性。     

The importance of business process modeling in software systems design

Despite diligent efforts made by the software engineering community, the failure of software projects keeps increasing at an alarming rate. After two decades of this problem reoccurring, one of the leading causes for the high failure rate is still poor process modeling (requirements’ specification). Therefore both researchers and practitioners recognize the importance of business process modeling in understanding and designing accurate software systems. However, lack of direct model checking (verification) feature is one of the main shortcomings in conventional process modeling methods. It is important that models provide verifiable insight into underlying business processes in order to design complex software systems such as Enterprise Information Systems (EIS). The software engineering community has been deploying the same methods that have haunted the industry with failure. In this paper, we try to remedy this issue by looking at a non-conventional framework. We introduce a business process modeling method that is amenable to automatic analysis (simulation), yet powerful enough to capture the rich reality of business systems as enacted in the behavior and interactions of users. The proposed method is based on the innovative language-action perspective.     

面向事实的概念建模方法研究综述

领域概念知识建模是构建信息系统分析的关键技术和任务之一,同时也是知识工程的瓶颈问题,其难点在于如何正确完整地捕捉和验证领域专家的知识。ER和UML等有属性特性的建模方法能够很好地描述领域知识,但却难以让领域专家确认知识的正确性和完整性。面向事实的信息建模(FOM)是一种完全面向自然语言交流的领域概念知识建模方法,是一种理想的概念建模和本体工程辅助工具。简要分析了概念建模过程,比较了不同概念建模方法,介绍了FOM的技术演化过程,从业务规则、动态建模、模型抽象机制、模型转换和工程应用等方面评述了FOM的研究现状和待研究问题。     

Derivational Analogy in PRODIGY: Automating Case Acquisition,Storage, and Utilization

Expertise consists of rapid selection and application of compiled experience. Robust reasoning, however, requires adaptation to new contingencies and intelligent modification of past experience. And novel or creative reasoning, by its real nature, necessitates general problem-solving abilities unconstrained by past behavior. This article presents a comprehensive computational model of analogical (case-based) reasoning that transitions smoothly between case replay, case adaptation, and general problem solving, exploiting and modifying past experience when available and resorting to general problem-solving methods when required. Learning occurs by accumulation of new cases, especially in situations that required extensive problem solving, and by tuning the indexing structure of the memory model to retrieve progressively more appropriate cases. The derivational replay mechanism is discussed in some detail, and extensive results of the first full implementation are presented. These results show up to a large performance improvement in a simple transportation domain for structurally similar problems, and smaller improvements when less strict similarity metrics are used for problems that share partial structure in a process-job planning domain and in an extended version of the strips robot domain.     

指令级密码处理器软件功耗建模与仿真

为了分析密码处理器软件的功耗,提高软件的抗能量攻击能力,提出了基于指令的处理器功耗建模仿真方法;详细阐述了模型建立、指令功耗求解算法以及指令功耗采集平台建立方法;在此基础上对一款密码专用处理器的AES加密算法软件功耗进行了仿真,对仿真结果和实际测量结果进行了比较分析,结果表明这种处理器功耗建模方法是有效的。     

基于角色的访问控制模型及其面向对象的建模

访问控制是信息安全的一个研究方向,基于角色的访问控制(RBAC)是目前理论研究和应用研究比较广泛的一种模型。详细介绍了RBAC96模型家族的特征和它所遵循的安全准则,并引入面向对象的思想,采用统一建模语言(UML)对RBAC96进行了静态和动态建模,这样就缩短了理论模型和实际系统开发之间的差距,有助于信息系统安全的面向对象的分析与设计。     

基于代数的软件过程建模系统的设计与实现

软件过程建模的主要目的是建立组织内软件开发过程的模型,使得软件开发过程在整个组织内获得一致的理解,进而提高软件开发效率和改进软件生产质量.软件过程建模语言一方面要易于理解、具有较强的表达能力,同时也要易于分析和验证,以保证所要描述的软件过程的正确性.介绍了基于代数的软件过程建模系统ASPMS的设计和实现,该系统提供了图形化的建模表示方式,而该图形化表示方式具有基于多元π演算的形式化语义,从而较好地平衡了建模语言的易于理解、具有较强的表达能力和易于分析和验证这一矛盾的内在要求.     

Steps towards a method for the formal modeling of dynamic objects

Fragments of a method to formally specify object-oriented models of a universe of discourse are presented. The task of finding such models is divided into three subtasks, object classification, event specification, and the specification of the life cycle of an object. Each of these subtasks is further subdivided, and for each of the subtasks heuristics are given that can aid the analyst in deciding how to represent a particular aspect of the real world. The main sources of inspiration are Jackson System Development, algebraic specification of data- and object types, and algebraic specification of processes.     

面向方面的信息系统建模方法及应用研究

随着面向对象软件开发技术的不断发展以及软件规模的不断扩大,系统地分析和设计变得日益复杂。软件开发过程中很难利用现有的编程技术（如面向对象编程、面向过程编程）对横切系统多个模块的关注点进行鉴别、理解和模块化。为解决面向对象开发方法中的耦合性较高、可重用性较低和代码分散等问题,将面向方面的编程思想引人到系统分析和设计阶段,提出了一种面向方面的信息系统建模方法。     

基于UML-RT的复杂嵌入式系统建模方法及其应用

分析了UML在实时系统设计中的优点和需要解决的主要问题,论述了基于UML RT的实时嵌入式系统设计方法,并且对其进行扩展以支持数据流计算模型的建模,最后以汽车巡航系统为例加以说明。     

An alternative approach in TMN interface modeling

The Open Systems Interconnection (OSI) architecture promotes techniques that reduce the interdependencies among components of a distributed cooperative system. This architecture requires restructuring of the traditional machine-to-machine interfaces to communicate effective information instead of transferring bulks of unstructured data. While this architecture increases the flexibility of the network and reduces the overhead associated with its evolution, it requires up-front work in designing the individual system interfaces. That is, an extensive plan and design for a system interface model are required to ensure the acceptance, evolution, and stability of interfaces and to allow the possibility of their graceful evolution. The purpose of this paper is to stimulate discussion over levels of abstraction in Object Oriented Representation (OOR). It provides examples on the impact of modeling approaches on systems evolution. Furthermore, it demonstrates that the TMN interface can be made more efficient if modeling is done at a higher level of abstraction.     

A case-based approach to software reuse

This software reuse system helps a user build programs by reusing modules stored in an existing library. The system, dubbed caesar (Case-basEd SoftwAre Reuse), is conceived in the case-based reasoning framework, where cases consist of program specifications and the corresponding C language code. The case base is initially seeded by decomposing relevant programs into functional slices using algorithms from dataflow analysis. caesar retrieves stored specifications from this base and specializes and/or generalizes them to match the user specification. Testing techniques are applied to the construct assembled by caesar through sequential composition to generate test data which exhibits the behavior of the code. For efficiency, inductive logic programming techniques are used to capture combinations of functions that frequently occur together in specifications. Such combinations may be stored as new functional slices.     

A case-based reasoning approach for building a decision model

A methodology based on case-based reasoning is proposed to build a topological-level influence diagram. It is then applied to a project proposal review process. The formulation of decision problems requires much time and effort, and the resulting model, such as an influence diagram, is applicable only to one specific problem. However, some prior knowledge from the experience in modeling influence diagrams can be utilized to resolve other similar decision problems. The basic idea of case-based reasoning is that humans reuse the problem-solving experience to solve new problems.
In this paper, we suggest case-based decision class analysis (CB-DCA), a methodology based on case-based reasoning, to build an influence diagram. CB-DCA is composed of a case retrieval procedure and an adaptation procedure. Two measures are suggested for the retrieval procedure, one a fitting ratio and the other a garbage ratio. The adaptation procedure is based on decision-analytic knowledge and decision participants' domain-specific knowledge. Our proposed methodology has been applied to an environmental review process in which decision-makers need decision models to decide whether a project proposal is accepted or not. Experimental results show that our methodology for decision class analysis provides decision-makers with robust knowledge-based support.