基于知识的机器人协同问题求解系统KBCOPS

本文在讨论了机器人协同问题求解的概念及难点的基础上，以模型化机器人世界为协同问题研究领域，选择并发成员系统程序设计语言ＭＳ－１为系统基本开发了一个基于知识的机器人协同问题求解系统ＫＢＣＯＰＳ，并给出了其在一维模型世界下的具体实现。     

计算机定量问题自动求解系统

“定量问题求解系统”，是ＡＩ和专家系统领域内的一门新技术。其目的是建立集科学、工程技术中广为应用的量、公式、定量等定理知识为一体的知识存储、检索和问题求解的计算机系统。本文简述国外计算机定量问题自动求解系统研究工作。全文介绍了定量问题求解系统的研究对象和一般的理论方法，并着重讨论几个典型的应用系统；同时详细介绍了一个用面象对象方法的开发的系统ＱＰＳ，该系统英国的Ｔｈｅ Ｑｕｅｅｎ’ｓ Ｕｎｉｖｅｒ     

基于知识的机器人协同问题求解系统KBCOPS

本文在讨论了机器人协同问题求解的概念及难点的基础上，以模型化机器人世界为协同问题研究领域，选择并发成员系统程序设计语言ＭＳ—１为系统基本开发环境，设计开发了一个基于知识的机器人协同问题求解系统ＫＢＣＯＰＳ（Ｋｎｏｗｌｅｄｇｅ—ＢａｓｅｄＣＯｏｐｅｒａｔｉｖｅＰｒｏｂｌｅｍＳｏｌｖｉｎｓＳｒｓｔｅｍ），并给出了其在一维模型世界下的具体实现。     

实现渔业资源评估专家系统的一种方法

本文介绍了一种用计算机专家系统实现我国东海渔业资源评估的方法。这一渔业资源评估专家系统是用面向对象的知识处理系统（ＯＫＰＳ）构造而成。ＯＫＰＳ是我们自主开发的一套可视化专家系统工具。本文着重阐述了ＯＫＰＳ系统和该专家系统的原理、模型选择的规则、专家知识库的构造与实现等问题。     

渗碳专家系统中的多专家求解问题的研究

本文研究了在渗碳专家系统中的问题求解策略，为了避免系统求解的主观性和片面性，提出了多黑板系统，例如问题黑板，辩论择优黑板，领域黑板和结论黑板作为问题的求解策略。使其非公认的渗碳领域问题通过专家进行辩论择优选出最佳解，为此提出建立基于多元组命题性知识的辩论理论框架，并体现不同策略的辩论算法，对此进行了计算机仿真，结果证明此方法是有效的。     

智能化114数据地图定位系统ISOPL

介绍一个智能化１１４数据地图定位系统ＩＳＯＰＬ。ＩＳＯＰＬ采用基于Ｃｏｎｔｅｘｔ的知识元结构表示问题求解的任务，使用推约推理方法进行问题求解的组织。ＩＳＯＰＬ不仅实现１１４数据的实时定位，同时，通过交互学习，可提高系统定位问题的求解能力和精度。     

应用面向对象知识处理的选案专家系统

本文介绍了一种用专家系统实现税务部门计算机稽查选案的方法。这一计算机选案专家系统是用面向对象的知识处理系统（ＯＫＰＳ）构造而成。ＯＫＰＳ是我们自主开发的一套可视化专家系统工具。本文着重阐述了ＯＫＰＳ系统和该专家系统的原理、选案知识库的构造、推理控制策略等问题。本文所讲解的这一计算机选案专家系统已作为广东地税信息系统（ＧＤＬＴＩＳ）的一部分投入实际运行。     

支持人工智能问题求解语言DMS通讯技术

本文阐述了ＤＭＳ通语的设计，它是基于产生式的系统ＯＰＳＳ的优点而克服其缺点，为了支持人工智能问题求解而设计的语言环境。     

面向对象的智能化FMS调度仿真

该文在分析传统数学方法和实验仿真方法的基础上，提出了一个求解ＦＭＳ调度问题的智能决策系统，使用面向对象的方法，构造了一个专家系统和仿真技术集成的调度模型，并进行了仿真实验分析。     

关系数据库实现面向对象数据库的方法

过去十多年，面向对象技术已应用于数据库，操作系统，专家系统等，有些面向对象数据库已经商品化，随着数据库应用领域的不断扩展，面向对象数据库系统已成为一个重要的研究领域，本文对现有的ＯＯＤＢＳ和ＲＤＢＳ作了一些比较，进而介绍了二者统一的途径。     

基于知识的多专家决策支持系统

由于决策支持系统（ＤＳＳ）和专家系统（ＥＳ）的不同行为特征,使它们在信息处理中的决策和问题求解方面不能相互兼顾。本文交讨论和ＥＳ结合的可行性,提出一种基于知识的多专家决策支持系统的结构模式,及实现多专家协同求解和决策的方法。     

一种基于规则的双层四边通道布线专家系统原型

四边通道布线问题(switchbox routing problem)是VLSI布图设计(layout)中的一个关键问题。从计算的观点看,它是一个NP-hard问题。因此,基于知识的方法是解决这一问题的有效方法。 本文中,提出了一种以PROLOG为核心的基于规则的双层四边通道布线专家系统的原型(prototype)。它能把人类布线专家的规划、推理能力及布线经验同计算机的高速数据处理能力有机地结合起来,从而取得较高的布线效率和布通率。     

An approach to expert control of interactive software systems

Expert problem-solving strategies in many domains require the use of detailed mathematical techniques coupled with experiential knowledge about how and when to use the appropriate techniques. In many of these domains, such techniques are made available to experts in large software packages. In attempting to build expert systems for these domains, we wish to make use of these packages, and are therefore faced with an important problem: how to integrate the existing software, and knowledge about its use, into a practical expert system. The expert knowledge is used, in dynamic selection and interpretation of appropriate programs and parameters, to reach a successful goal in the problem solving. We describe the framework of a hybrid expert system for representing problem-solving knowledge in these domains. This hybrid system may be characterized as consisting of a production system and mathematical methods. The software package is reorganized as necessary to map it into the mathematical-method representation of a hybrid system. This approach has evolved out of an effort to build an expert system for performing well-log analysis, ELAS (expert log analysis system).     

ON KNOWLEDGE REPRESENTATION FOR INFERENCES IN CAST METHOD BANKS

This article explains why aspects of knowledge representation must be considered in the context of computer aided systems theory (CAST). CAST method banks support human experts during the process of problem solving. They should be understood as decision support systems, as assistants of their human expert users. One key to making this approach work is the communication between the expert and the system. The assistant should provide systematical and goal-directive information about the current problem state for the human expert. Another, even more important requirement is the assistant's knowledge about all available methods at a certain problem-solving state and their expected impact on the further problem-solving process. Knowledge representation denotes how the problem domain is represented within the support system and how it is used. We investigate different forms of knowledge representations and summarize criteria for the applicability of different forms of knowledge representations in CAST systems.     

Simulation economic evaluation: An expert system for workshop simulation

The job-shop scheduling optimization problem is an example application of Operations Research and Simulation models. This problem has been extensively researched and different models have been presented in the literature for solving different situations. SLAM (Simulation Language for Alternative Modeling) 4 is a simulation language that can be used to analyze this problem and is now available for microcomputers. However, SLAM, similar to the other specialized simulation languages, requires sophisticated analysts to transcribe the problem in SLAM commands.

This paper presents an expert system that can generate SLAM commands for a job-shop planning application where a user with no SLAM or Simulation knowledge can interact directly with a micro-computer to run the SLAM application. The expert system is in the form of a user-friendly conversational program which automatically translates the problem parameters into SLAM commands, executes the SLAM program, and provides an unsophisticated Simulation user with the analysis results.     

THE DISCIPLE–RKF LEARNING AND REASONING AGENT

Over the years we have developed the Disciple theory, methodology, and family of tools for building knowledge-based agents. This approach consists of developing an agent shell that can be taught directly by a subject matter expert in a way that resembles how the expert would teach a human apprentice when solving problems in cooperation. This paper presents the most recent version of the Disciple approach and its implementation in the Disciple–RKF (rapid knowledge formation) system. Disciple–RKF is based on mixed-initiative problem solving , where the expert solves the more creative parts of the problem and the agent solves the more routine ones, integrated teaching and learning , where the agent helps the expert to teach it, by asking relevant questions, and the expert helps the agent to learn, by providing examples, hints, and explanations, and multistrategy learning , where the agent integrates multiple learning strategies, such as learning from examples, learning from explanations, and learning by analogy, to learn from the expert how to solve problems. Disciple–RKF has been applied to build learning and reasoning agents for military center of gravity analysis, which are used in several courses at the US Army War College.     

运用Web Service技术构建专家系统之间的交互

专家系统解决问题的范围常常受到知识领域狭窄的限制。Web Service实现了“基于Web无缝集成”的目标,可以运用Web Service技术来实现专家系统之间的交互,弥补专家系统知识不足的问题。文中运用Web Service提供的技术构建网络上专家系统之间的交互,并且对这种交互的可行性进行了分析研究,这就不仅为解决专家系统知识不足的问题提供了方法和技术,而且进一步构建了一个模型,使得网络上专家系统互相协作,共同解决一个领域更广的问题。     

The explanation facility and the explanation effect

The ability to explain reasoning processes used for problem solving distinguishes the expert system from other decision support systems. The explanation facility is intended to help the user critically analyze the expert system output. Studies investigating the explanation effect, however, report that the act of explaining an event's occurrence increases the perceived likelihood of the event. The consideration of expert system explanations, therefore, may lead to greater agreement with the system's output rather than the intended critical review of the output. This research examines the explanation effect resulting from the consideration of expert system explanations. The differential impact of considering expert system explanations is compared to the effect of generating written explanations. In addition, the differential impact of positive versus negative explanations is investigated. A hypothetical audit case was administered to 41 practicing auditors. An explanation effect was observed when the expert system explanation was negative. An explanation effect was not observed when the expert system explanation was positive. An explanation effect was not observed for either positive or negative self-generated explanations. Therefore, the most influential explanations were those which were expert system generated and negative or conservative in direction.     

OEC：一个面向对象的专家系统构造工具

本文提出了一种面向对象的专家系统构造方法，利用面向对象的程序设计的封装性，继承性等特点，实现了多种问题求解方法的统一的环境，并为专家系统构造工具的简单性与灵活性的结合提供了一条途径。     

再设计问题的求解策略

本文详细研究了应用相关性制导回溯实现设计类专家系统再设计控制策略的理论和方法。研完了应用正确性维持系统记录导出事实的相关性论据、实现知识库的一致性检查和维护、利用相关性论据提供回溯点信息的方法。提出将数据库理论中版本管理技术应用于设计类专家系统的事实库管理,讨论了事实库版本管理对推理所产生的作用。