知识云及其在知识获取中的意义

如何有效地获取领域专家的知识一直被视为人工智能中的难题．本文的目的在于提出一种关于知识获取的基本观点，并以此观点为基础来研究知识获取问题．这个观点的基本内容是：象波尔的原于模型一样，在专家的知识周围有一些知识层．它们是认识和获取专家知识的突破口或入口．本文将这些知识层看成是知识云，同时将上述观点视作知识云假设．我们将讨论知识云的内涵，研究知识云假设的合理性，最后将阐述知识云这一概念在知识获取中的意义．     

Knowledge types: a practical approach to guide knowledge engineering in domains of building design

Abstract: This paper presents experiences and findings achieved through several expert system projects in domains of technical buiding design. The main focus is on knowledge acquisition and knowledge decomposition. Different approaches are presented and discussed. Four types of knowledge are presented: object knowledge, performance knowledge, event knowledge and metaknowledge, and the applicability of this classification to building design is justified. The paper includes a listing of experiences gained by real world testing of an expert system, and finally we outline guidelines to knowledge engineering in the domain of technical building     

知识获取方法DECO

知识获取方法学是目前人工智能领域中最重要的分支之一,现在已出现了几种不同应用范围的获取方法,集成式知识获取方法的研究已成为当前的一种趋势,本文所介绍的DECO方法是一种集成式方法,它将知识获取分为若干个基本上相互独立的步骤,并且溶进了知识库快速生成技术以及基于专家分析实例的学习方法。     

VALIDATION OF FIRST-ORDER RULE-BASED SYSTEMS1

Knowledge base validation and knowledge base refinement aim to help the expert to improve an existing knowledge base. They deal with the final knowledge acquisition phase and rely on a quality measurement of an existing knowledge base. We present our approach to knowledge base refinement, which is based on results in the domain of knowledge base validation. Our approach is based on a general consistency definition of a knowledge base and on a study of causes of knowledge base inconsistency. Our approach relies significantly on a differentiation of sure and expert knowledge in the knowledge base. We have implemented a system that has two phases: one computational phase decides on the consistency of a knowledge base, and, if necessary, a second phase helps the expert to interactively update the knowledge base. We present some related work in the domain. We illustrate the use of our system with an example.     

基于场景及规则获取模板的知识获取方法

产生式规则作为知识库系统进行推理的常用的、可读性好的知识表示形式,在构建知识库系统时有极大的优越性.提出一种基于场景及规则获取模板的知识获取方法,并以某高分子复合材料的加工专家为知识获取对象.该方法通过分析、记录领域专家进行设计的过程、解决问题的过程和动作,将领域问题按层次细化为一系列子问题,并在子问题场景下结合场景模型及知识获取模板来获取规则性知识.采用该方法可以辅助领域专家在明晰领域知识结构的基础上,逐步挖掘领域中细粒度的规则性知识.     

Using natural language sources in model-based knowledge acquisition

This paper introduces a well defined co-operation between domain expert, knowledge engineer, and knowledge acquisition and transformation tools. First, the domain expert supported by a hypertext tool generates an intermediate representation from parts of authentic texts of a domain. As a side effect, this representation serves as human readable documentation. In subsequent steps, this representation is semi-automatically transformed into a formal representation by knowledge acquisition tools. These tools are fully adapted to the expert's domain both in terminology and model structure which are developed by the knowledge engineer from a library of generic models and with preparation tools.     

Expert knowledge acquisition and the unwilling expert: a knowledge engineering perspective

Expert systems are an evolving technology with the potential to make human expertise widely and cheaply available. The literature describing the development of expert systems generally assumes that experts willingly give up their knowledge. This is unrealistic and may be a reason why most expert system projects fail. This paper explores the problem of unwilling experts from the perspective of a knowledge engineer building an expert system. The link between knowledge and organizational power is established and human motivation theories are discussed. Finally, a new motivational approach is introduced to help the knowledge engineer deal with unwilling experts.     

An Analysis of Knowledge Acquisition Roles and Participants

Much recent research effort in the field of knowledge acquisition (KA) has focussed on extending knowledge acquisition techniques and processes to include a wider array of participants and knowledge sources in a variety of knowledge acquisition scenarios. As the domain of expert systems applications and research has expanded, techniques have been developed to acquire and incorporate knowledge from groups of experts and from various sources such as text, video, and audio tapes. However, the dominant participant-role model remains that of the knowledge engineer eliciting knowledge from one or more human experts. This conceptual gap has contributed to the major divisions in the KA field between researchers interested in manual KA and those developing tools for automated KA. This article considers the wide variety of possible KA scenarios and presents a meta-view of KA participants and the roles they may assume.We suggest that it is more appropriate to think of knowledge acquisition participants as playing one or more roles. These include knowledge sources, agents and targets for KA processes. We also present a participant model drawn from research in decision support systems that more accurately characterizes the diversity of the entities participating in the KA process. This view is more inclusive as it allows us to consider both human-human and human-computer KA interactions as well as the whole variety of knowledge sources and targets. A careful consideration of the meta-view and its associated role-participant mappings also yields the new ideas of the elemental and composite role and the multi-role entity. These new constructs are then used to identify areas where research is currently needed and to generate specific research issues. Taken altogether, this view allows a more flexible consideration of the many possible combinations that can and frequently do occur in actual KA situations.     

基于神经网络专家系统的研究与实现

针对传统专家系统推理能力弱和智能水平低等不足,本文采用神经网络方法解决了传统专家系统在知识表示和知识获取等方面的问题。本文从描述传统专家系统几点不足出发,详细阐述了神经网络专家系统的基本原理和框架结构,最后选取三层BP神经网络模型,给出了钻井故障诊断系统的神经网络专家系统的实现。     

ROGET: A knowledge-based system for acquiring the conceptual structure of a diagnostic expert system

This paper describes ROGET, a knowledge-based system that assists a domain expert with an important design task encountered during the early phases of expert-system construction. ROGET conducts a dialogue with the expert to acquire the expert system's conceptual structure, a representation of the kinds of domain-specific inferences that the consultant will perform and the facts that will support these inferences. ROGET guides this dialogue on the basis of a set of advice and evidence categories. These abstract categories are domain independent and can be employed to guide initial knowledge acquisition dialogues with experts for new applications. This paper discusses the nature of an expert system's conceptual structure and describes the organization and operation of the ROGET system that supports the acquisition of conceptual structures.     

专家系统中基于粗集的知识获取、更新与推理

知识获取、知识更新和不确定性推理是设计专家系统的重要方面。根据粗集理论，提出了一种专家系统的结构模型，该系统在规则获取的基础上，利用系统运行的实例增量式地更新知识库中的规则及其参数，以改善系统的性能，利用知识库中的规则及数量参数进行不确定性推理，得出结论的可信度。     

Integrated graphical approach to knowledge representation and acquisition

An approach toward improving the accessbility of the knowledge and information structures of expert systems is described; it is based upon a foundation development environment called the Rule-Based Frame System (RBFS), which forms the kernel of a larger system, IDEAS. RBFS is a knowledge representation language, within which a distinction is drawn between information which represents the world or domain, and knowledge which states how to make conclusions based upon the domain. Information takes the form of frames, for system processing, but is presented to the user/developer as an associative network via a Visual Editor for the Generation of Associative Networks (VEGAN). Knowledge takes the form of production rules, which are connected at suitable points in the domain model, but again it is presented to the user via a graphical interface known as the Knowledge Encoding Tool (KET). KET is designed to assist in knowledge acquisition in expert systems. It uses a combination of decision support trees and associative networks as its representation. A combined use of VEGAN and KET will enable domain experts to interactively create and test their knowledge base with minimum involvement on behalf of a knowledge engineer. An inclusion of learning features in VEGAN/KET is desirable for this purpose. The main objective of these tools, therefore, is to encourage rapid prototyping by the domain expert. VEGAN and KET are implemented in the Poplog environment on SUN 3/50 workstations.     

基于虚拟样机的故障知识获取研究

文章利用CATIA软件对某型导弹发射装置发射台建模并利用工程分析模块Analysis＆Simulation进行有限元分析,获得导弹发射装置在载荷变化情况下的可视化资料,获取载荷一故障之间的对应关系,建立智能诊断专家系统知识库,为解决机电设备故障诊断专家系统知识获取的“瓶颈”问题提供了一个新的思路。     

On two AI traditions

To understand the role of expert systems as a medium for transferring knowledge and skills within organisations requires an understanding of the nature of expertise within working life contexts. Central to this issue of transfer is the debate on the nature of tacit/implicit knowledge and the problem of formalising it in explicit form. This paper considers the British approach to the development of knowledge-based systems, which is regarded as being predominantly rationalistic, and compares it with the Scandinavian approach, which is regarded as being predominantly humanistic. The paper proposes that crucial to the debate on the transfer of knowledge and skills is the development of expert systems as communications media which aims at enhancing and sharing the knowledge and skills of users. A human-centred approach for the future is proposed which brings the above two traditions together thereby providing a developmental framework for knowledge based systems.     

Integrated knowledge acquisition architectures

An architecture for knowledge acquisition systems is proposed based upon the integration of existing methodologies, techniques and tools which have been developed within the knowledge acquisition, machine learning, expert systems, hypermedia and knowledge representation research communities. Existing tools are analyzed within a common framework to show that their integration can be achieved in a natural and principled fashion. A system design is synthesized from what already exists, putting a diversity of well-founded and widely used approaches to knowledge acquisition within an integrative framework. The design is intended to be clean and simple, easy to understand, and easy to implement. A detailed architecture for integrated knowledge acquisition systems is proposed that also derives from parallel cognitive and theoretical studies.     

基于电路仿真的故障知识获取研究

本文利用电路软件Multisim2001对某型导弹发射车的电控系统电路进行仿真,通过仿真获得导弹发射车的电控系统电路的故障参数,获取功能-故障之间的对应关系,建立智能诊断专家系统知识库,为解决专家系统知识获取的“瓶颈”问题提供一个新的思路。     

基于运动仿真的故障知识获取研究

本文利用机械制造与设计软件PRO/EMechanism模块对某型发射车建模并利用装配模块将其安装,进行运动仿真,获得导弹发射车的发射程序过程的可视化资料,获取运动-故障之间的对应关系,建立智能诊断专家系统知识库,为解决专家系统知识获取的“瓶颈”问题提供一个新的思路。     

Knowledge engineering revisited

About six years ago a paper on Knowledge Engineering was published in this Journal. This paper attempts to extend and elaborate on the ideas and concepts discussed earlier. Four major problems are addressed: Preservation of knowledge, proliferation of knowledge, dissemination of knowledge, and application of knowledge. The design principles for both rule-based expert systems and pattern-directed expert systems are discussed and compared.     

专家系统中背景研究的意义

人工智能中不同领域的研究表明：新一代的智能辅助系统是与背景相关的。虽然人们普遍接受知识应有一个背景部件的观点，但在可用的知识表态方法及随后的知识处理中极少显式表达和利用背景知识。本文着眼于探讨 背景研究在专家系统开发中的意义，以期阐明：背景知识的显式识别、表达与利用有助于专家系统听知识获取、知识表示、推
推理、学习和解释，从而提高专家系统自适应能力和解决问题的智能性。