Human operators and real-time expert systems

Abstract: This paper describes and examines real-time expert systems from the perspective of their users. It categorizes real-time expert systems according to a three-component system consisting of an expert system, a user and a process being controlled, by considering all possible arrangements of information flow between the components, and uses this classification as a basis for reviewing real-time expert systems. The focus of interest lies in those characteristics of real-time expert systems which impinge on users, especially as they have been discussed by computer scientists. After critically examining these claims, the paper discusses the interaction between systems and users at the perceptual/motor, cognitive and supervisory levels. It concludes by arguing that the successful design and installation of real-time expert systems require the application of ergonomics techniques to provide for efficient and accurate user-system interaction.     

Human factors in information technology: The socio-organisational aspects of expert systems design

This paper looks beyond the mostly technical and business issues that currently inform the design of knowledge-based systems (e.g., expert systems) to point out that there is also a social and organisational (a socio-organisational) dimension to the issues affecting the design decisions of expert systems and other information technologies. It argues that whilst technical and business issues are considered before the design of Expert Systems, that socio-organisational issues determine the acceptance and long-run utility of the technology after it has been implemented. It shows how four issues within the organisation can affect the design or the after-effects of the design and implementation of the technology. It also shows how the four issues can be considered within the structured phases of expert system development.     

MAG-EX: A magnetics fabrication expert systems focusing expert systems technology on improving quality control

This paper describes the development and experiences involved with creating a prototype application for the use of expert systems technology in manufacturing, specifically in quality control. The company described in the paper is an electronics manufacturer specializing in power supplies and amplifiers for military and commercial applications. It currently relies heavily on traditional manufacturing information systems technology. Quality control must meet DoD and other regulations and directly affects the bottom-line. As a potential expert system project, management felt as though product quality and the company as a whole could benefit from strategic development in Quality Assurance. The paper discusses the process, the difficulties, and the derived benefits to quality control from the development of an expert system application. Further, the paper reports on additional training benefits derived from the explanation capability of the expert system.     

Implementing expert systems technology: a corporate-wide approach

Abstract

At present, expert systems (ES) technology is used opportunistically by organizations mainly on an individual application basis. As a result, assimilation of this technology can be slow as there is no proper co-ordination. With increasing awareness of its value and benefits, more organizations are venturing into this technology, but to maximize its potential, a systematic approach must be adopted. This study examines an organized corporate-wide approach designed by a major corporation in Singapore to exploit ES technology. Besides technical issues, the analysis revealed numerous human behavioural variables pertinent to the construction of the master plan. The corporate culture and its present level of computerization, which are related to the psychological readiness of its staff members to tap into ES technology on a more massive scale, arc significant factors. The entire study is put into perspective by using technology assimilation models such as those of McFarlan. McKenny. and Pyburn.     

Implementing expert systems technology: a corporate-wide approach

At present, expert systems (ES) technology is used opportunistically by organizations mainly on an individual application basis. As a result, assimilation of this technology can be slow as there is no proper co-ordination. With increasing awareness of its value and benefits, more organizations are venturing into this technology, but to maximize its potential, a systematic approach must be adopted. This study examines an organized corporate-wide approach designed by a major corporation in Singapore to exploit ES technology. Besides technical issues, the analysis revealed numerous human behavioural variables pertinent to the construction of the master plan. The corporate culture and its present level of computerization, which are related to the psychological readiness of its staff members to tap into ES technology on a more massive scale, arc significant factors. The entire study is put into perspective by using technology assimilation models such as those of McFarlan. McKenny. and Pyburn.     

网格资源管理系统模型的研究

针对已有模型不能实现更多范围内获取所需要的资源,提出了一个改进的通用抽象体系结构模型,通过接口向网格资源管理系统发布、获取自己所需要的资源,实现用户在更大范围内获取所需要的资源.创建了该模型的原型系结构模型,通过接口向网格资源管理系统发布、获取自己所需要的资源,实现用户在更大范围内获取所需要的资源.创建了该模型的原型系统的网格,并在该网格上进行了一些算法研究.实验结果证实了该实践中的可行性和优越性.     

多项目资源管理技术研究

为了帮助企业在多个项目同时实施的情况下合理、有效地配置各种资源,提高资源利用率,研究了多项目多资源的资源均衡问题,给出了解决此类问题的基本方案.分析了几种传统理论与方法优缺点,指出其中不足,设计了一种改进的遗传算法,并通过仿真验证了其在解决资源均衡问题上的高效性与可行性.在此基础上,设计了一个多项目资源管理系统框架,该系统框架使用遗传算法实现资源均衡性优化,从而提供了多项目资源管理中经常使用的工具.     

Uncertainty management in expert systems using fuzzy Petri nets

The paper aims at developing new techniques for uncertainty management in expert systems for two generic class of problems using fuzzy Petri nets that represent logical connectivity among a set of imprecise propositions. One class of problems deals with the computation of fuzzy belief of any proposition from the fuzzy beliefs of a set of independent initiating propositions in a given network. The other class of problems is concerned with the computation of steady-state fuzzy beliefs of the propositions embedded in the network, from their initial fuzzy beliefs through a process called belief revision. During belief revision, a fuzzy Petri net with cycles may exhibit “limit cycle behavior” of fuzzy beliefs for some propositions in the network. No decisions can be arrived at from a fuzzy Petri net with such behavior. To circumvent this problem, techniques have been developed for the detection and elimination of limit cycles. Further, an algorithm for selecting one evidence from each set of mutually inconsistent evidences, referred to as nonmonotonic reasoning, has also been presented in connection with the problems of belief revision. Finally, the concepts proposed for solving the problems of belief revision have been applied successfully for tackling imprecision, uncertainty, and nonmonotonicity of evidences in an illustrative expert system for criminal investigation     

An evaluation of expert systems for software engineering management

The development of four separate, prototype expert systems to aid in software engineering management is described. Given the values for certain metrics, these systems provide interpretations which explain any abnormal patterns of these values during the development of a software project. The four expert systems which solve the same problem, were built using two different approaches to knowledge acquisition, a bottom-up approach and a top-down approach and two different expert system methods, rule-based deduction and frame-based abduction. In a comparison to see which methods might better suit the needs of this field, it was found that the bottom-up approach led to better results that did the top-down approach, and the rule-based deduction systems using simple rules provided more complete and correct solutions than did the frame-based abduction systems     

Artificial worlds modeling of human resource management systems

Effective human resource management facilitates the success of an organization and the progress of a society. We describe an evolutionary computer model that simulates different modes of interaction between people and their environment. A two-level genotype-phenotype structure is used to represent the characteristics of an individual. The environment is modeled as a two-dimensional array of regions in which each region is characterized by a set of regional features and organizational culture. Evolution can occur at the regional and organizational levels. At the level of regional learning, the experimental results show that people tend to migrate from lesser-fitting regions to better-fitting regions to increase their fitness, which in turn results in the problem that some regions become extremely crowded and other areas have few residents. This problem can be partially eased by putting pressure on the number of people allowed in each region. However, our results show that too great an increase in pressure worsens the problem. At the level of organizational learning, our experiments show that individuals with a local mutation operator are better at adapting to a constant leadership strategy (type), while those with a global mutation operator are better at coping with the changes in leadership strategy. The individuals who sustain a balance between a global and a local mutation operator achieve better performance in a changing leadership strategy than a constant leadership strategy. The results demonstrate that the model is imparted with sufficient dynamics to allow different types of outputs to occur. The artificial worlds approach makes it possible to conduct some experiments that are infeasible to perform in the real world. Combining more selected features into the model would show its potential use in investigating complex human resource management issues.     

Problem-oriented systems as a resource of paperless decision-making technology

Conclusions It is difficult in the framework of one article to generalize and systematize the rich factual material of investigations of traditional sore points in programming: the development of convenient languages and efficient systems, increasing reliability and quality of programs and their complexes, automating the process of generating PO systems, implementing teleacess resources, and unification and standardization. Nevertheless, in light of the questions examined in the past twenty years [32, 33] the basic aim of system programming must be perceived in attaining paperless decision-making technology. The basic concepts of this technology were formulated in the last monograph of Glushkov [1], in which he indicates that further increase of the potential of administrative mechanics and scientific investigations ... may not be attained in the framework of traditional (paper-based) technology owing to the fact that people will be supplied with these or those instruments that act as deposits, i.e., when all information flows are enclosed in a finite loop through people. Reserves in the growth of labor productivity with such technology are quickly exhausted owing to bottlenecks that restrict the throughput of the human element.Translated from Kibernetika, No. 1, pp. 11–21, January–February, 1985.     

Strategic justification of advanced automated technology systems using an expert system

This paper presents an application of expert systems for the strategic justification of advanced automated technology systems. This expert system is developed using the EXSYS expert system shell in the VAX-VMS mainframe environment. It considers important attributes such as suitability (measure of the AMT's compliance with corporate strategy); system capability; performance of the AMT system; and productivity including the financial benefits of the AMT.     

Agent技术在人力资源管理上的应用

为了实现人力资源管理信息系统的进一步智能化,尤其使它在决策支持的实际工作中发挥更大的作用,简要分析了传统人力资源管理信息系统中存在的主要问题,结合Agent和多Agent的特点阐述了Agent技术在解决这些问题上具有的优势,对如何将Agent技术应用到人力资源管理中去进行了探讨,提出了一种新的人力资源管理信息系统实现方案。     

Human experts and expert systems: A view from the shop-floor

For quite some time, the research in artificial intelligence has focused on expert systems, because here are to be found practical applications at the experimental stage which may soon become widespread. This focus makes more pressing the need to link the debate about the fundamental efficiency of artificial intelligence with those activities that aim at the application of specialized expert systems. In this paper, I begin by considering the stages and the development of human expertise. As a frame of reference I propose a polar dialectic model of the development of human acting and thinking that explicitly deals with the interplay of calculating rationality and intuition. This suggests the use of expert systems as decision aids particularly in the field of maintenance work on the shop-floor. With regard to this case, some theses concerning the human-centred shaping of technology and work are presented.     

Multi-domain expert systems

Abstract: The current trend in expert system building is domain-specific, i.e. there is one expert system for each problem domain. The increased involvement of computers in the decision-making process will inevitably lead to increased demand for expert systems. Based on the current approach to expert systems building, there will be a further proliferation of domain-specific expert systems. This is because each application area produces an expert system tailored to its requirements. This manner of producing expert systems is inadequate and an increased expectation in the performance of expert systems will eventually call for a new approach to constructing them. This paper examines the growth in the use of expert systems, looks into the limitations and problems associated with present-day domain-specific expert systems and suggests a multi-domain expert system architecture as a solution to the problem of increasingly disjointed domain-specific expert systems resulting from uncontrolled proliferation.     

Statistical expert systems

Abstract: Two types of expert system which involve statistical expertise are statistical consulting programs and programs which find patterns in databases. Consulting programs can now be built quickly using programming tools. Most expert systems include mechanisms for reasoning under uncertainty. Methods under investigation include fuzzy logic, Dempster-Shafer theory, Bayesian analysis and various ad hoc methods. Learning systems use statistics to infer inductive rules, and statistical reasoning can also be used to evaluate the performance of expert systems. The use of a prototype statistical expert system, XSAMPLE, is demonstrated, as a system to handle a consulting session with a statistically moderately advanced user.     

Evaluating expert systems

Abstract: Evaluation is crucial for improving expert system design and performance. This paper stresses the need for considering system evaluation throughout the development process. It highlights the importance of evaluating system usability and discusses key usability issues. A number of basic evaluation methods are described, including interviews, questionnaires, observation, system logging, user diaries, laboratory experiments and field trials. Finally, the paper looks at evaluating systems within organisations, and assessing other long term effects of expert systems.     

Internet-based expert systems

The Internet offers a large potential for delivery of various information-based services, including the services of intelligent applications. As the availability of the Internet has grown, its value as a medium for the delivery of expert systems in particular has increased. There are now a large number of expert systems available on the Internet, including applications in industry, medicine, science and government. Though the Internet provides several advantages for expert system development, it also presents some special problems. These advantages and disadvantages are explored in more detail in this paper. The paper also presents a review of several Internet-based expert systems with a representative sample of publicly available applications, and a discussion of typical tools for developing Internet-based expert systems. A case study of an Internet-based expert system is presented as well.