KNOWLEDGE ACQUISITION METHODOLOGIES: SURVEY AND EMPIRICAL ASSESSMENT

Knowledge acquisition, the process of extracting information from human experts, is one of the challenges in building expert systems. Modern practitioners and researchers need more guidance than is provided by existing knowledge acquisition guidelines. However, there has been little empirical research upon which to base the needed guidelines. This paper surveys the available knowledge acquisition techniques and describes a knowledge acquisition experiment which contrasts three of these methods. A framework was developed to categorize the types of heuristic which can be elicited with different means of knowledge acquisition. This research represents the initial steps in a research program focused on the development of empirically evaluated, generalized guidelines for effecting .knowledge acquisition

Assessment of Intelligence Complexity in Embedded Intelligent Real Time Systems

Intelligent systems and their applications are proliferating. Embedded Intelligent Real-Time Systems (EIRTS) are one type of intelligent system. Defining and measuring the complexity of this kind of system may help with better design, development, maintenance, and performance of EIRTS. In this paper, we propose a set of evaluation criteria to measure the complexity of Embedded Intelligent Real-Time Systems (EIRTS). We show an operationalization of the criteria with a sample EIRTS

Impact of a Distributed Intelligent System in a Large Scale Safety Critical System

Safety critical large scale systems are complex, physically extensive socio-technical systems, extending over a range of domains, and are of interest because of the enormous catastrophic potential on their constituents, bystanders and the environment. Often, failures in such systems are traced to human error, as well as to unforeseen and unanticipated combinations of causal factors arising from the size, scope and complexity of the systems. Technologies developed to support these systems are often distributed, supporting subsystems with specific local requirements

Safety Critical Wide Area Network Performance Evaluation

The growing importance of real-time computing in numerous applications poses problems for network architectures, especially safety-critical Wide Area Networks (WANs). Assessing network performance in safety-critical real-time systems is difficult, and suggests the use of both human and technical performance criteria because of the importance of both dimensions in safety-critical settings. This research proposes a model that considers both technical and human performance in network evaluation