A defeasible reasoning framework for human mental workload representation and assessment

Human mental workload (MWL) has gained importance in the last few decades as an important design concept. It is a multifaceted complex construct mainly applied in cognitive sciences and has been defined in many different ways. Although measuring MWL has potential advantages in interaction and interface design, its formalisation as an operational and computational construct has not sufficiently been addressed. This research contributes to the body of knowledge by providing an extensible framework built upon defeasible reasoning, and implemented with argumentation theory (AT), in which MWL can be better defined, measured, analysed, explained and applied in different human–computer interactive contexts. User studies have demonstrated how a particular instance of this framework outperformed state-of-the-art subjective MWL assessment techniques in terms of sensitivity, diagnosticity and validity. This in turn encourages further application of defeasible AT for enhancing the representation of MWL and improving the quality of its assessment.     

Representing Navy tactical computer system knowledge for reengineering and integration

This article describes an ongoing project in representing knowledge about Navy tactical computer systems. The primary concern is for their continuing evolution and/or integration with other tactical systems. Following an introduction to this class of application and a review of how the Naval Surface Warfare Center is addressing the issue of extending the investment in these systems, the software process is examined and two alternative, incompatible paradigms are presented. The latter, which relies on the use of software knowledge, is described briefly, and an environment that implements this paradigm is presented as a proof of concept. Because the transfer of this paradigm to the desired Navy applications will not be completed in the near future, the article concludes with the presentation of a general framework for classifying Navy reengineering projects that should improve assessment and also aid in the building of a knowledge base to support the improved process model.Mr. Blum's work was supported in part by the U.S. Navy, Space and Naval Warfare Systems Command (SPAWAR) under contract N00039-89-C-0001, task VMAR9 with the Office of Naval Research (ONR) and the Naval Surface Warfare Center (NAVSWC).Ms. Moore's current affiliation is with the Defense Information Systems Agency, Arlington, VA 22204-2199. The opinions expressed in this paper do not necessarily reflect the views of the Defense Information Systems Agency.     

Framework of knowledge-based systems : Multiple meta-level architecture for representing problems and problem-solving processes

Currently available expert systems have a performance limit because of the lack of capability to describe problems and problem-solving methods. It is closely related with knowledge representation language, but this is not the only concern with this issue. Real world problems and problem-solving methods are not so simple as to be represented always in the same way by the same language. Their representations must be different depending on various factors involved in the problems themselves and the situations these problems are surrounded with. In this paper, the author discusses first the intrinsic nature of problem representation and problem-solving process representation. The requirements for and the conceptual framework of a knowledge-based system that is suited for dealing with various problems then become apparent quite naturally. The author asserts that a multiple meta-level architecture is necessary as well as a knowledge-representation language that can describe complex data structures as the basic framework of knowledge-based systems.     

知识模型的拓扑变换

综述了知识表示方法中现行的变换技术，指出了其局限性，并提出了一种既便于问题求解，又易于问题求解的新变换技术──知识模型的拓扑变换。     

Robot selection expert ‘Rose’

One of the major problems facing the robot user in the future will be his choice of the optimum robot for a particular task. What is needed is a highly automated robot selection system which will eliminate the human decision-making process. The system presented will be used when a robot is being considered to replace a human at a particular task, while the rest of the workplace remains fixed. The purpose of this paper is twofold; firstly, to demonstrate the knowledge required in making an optimum robot selection, and secondly, to provide a tutoral in designing an expert system using EXPERT. The paper will provide (1) the data base, (2) rules for transforming that data base, and (3) the control strategy that is necessary in implementing an expert system to perform the aforementioned task. The system will query the user as to the characteristics of the desired robot and the expert system will choose an optimum robot from the choices in the data base. The user will construct the environment in which the robot will be working by using 3-D modeling techniques. The user will choose from a menu and place the various objects which the robot will have to conform to. Thus, constraints such as maximum space available, can be stripped out of the 3-D drawing rather than having the expert system query the user for dimensions. One very good feature of such a system is that as new robots are developed their specifications can be added to the data base very easily.     

电力系统故障判断骨架型专家系统──故障模型知识库

讨论了电网故障判断专家系统工具中的知识表示方法和故障推理模型知识库的开发。知识表示采用框架表示方法，同时结合各种接线形式的特点，表示信息全面、明晰。在综合分析电网故障判断专家经验和启发性知识的基础上，提出多种故障的推理模式，并具体讨论了多种模型的结构及其实现方法。