Programming expert systems in OPS5: an introduction to rule-based programming
Programming expert systems in OPS5: an introduction to rule-based programming
A guide to expert systems
The role of frame-based representation in reasoning
Communications of the ACM
Communications of the ACM
Communications of the ACM
Artificial Intelligence
Artificial Intelligence
Building expert systems
Constraint-directed search: a case study of job-shop scheduling
Constraint-directed search: a case study of job-shop scheduling
Status report of the graphic standards planning committee
ACM SIGGRAPH Computer Graphics - Status report of the graphic standards planning committee
Guidon-Watch: A Graphic Interface for Viewing a Knowledge-Based System
IEEE Computer Graphics and Applications
An examination of a frame-structured representation system
IJCAI'79 Proceedings of the 6th international joint conference on Artificial intelligence - Volume 2
Techniques for sensor-based diagnosis
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
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Abstract: There is a significant amount of interest in expert systems and the software tools that are available for developing these systems. Most tools that are developed at university research labs are described in some detail in books, articles, or technical reports. However, there is a need for objective information on commercial software tools for building expert systems. These tools can be used for research, prototyping and developing end-user applications. Necessarily we must establish a set of criteria which can be used to evaluate these tools. These criteria include an evaluation of the basic features, the development environment, what a tool can be used for, how easy it is to learn and use, how much it costs, and how it is supported. In the first part of this paper, a set of criteria is described for evaluating expert system software tools. In the second part, these criteria are used to evaluate several currently available commercial tools. © 1986 Wiley Periodicals, Inc. (Mark H. Richer: Mark H. Richer is a Scientific Programmer with the Knowledge Systems Laboratory of the Computer Science Department at Stanford University. His main responsibility is to contribute to the design, implementation, evaluation and maintenance of software for the Guidon project, including the Neomycin medical diagnosis system and the Guidon-2 instructional programs. He has received the MS in computer science and the MA in interactive educational technology, both from Stanford University. He has also earned the B.A. in Psychology from SUNY Binghamton and a California teaching credential from SF State University. Prior to graduate work at Stanford, Richer coordinated a microcomputer lab at a public elementary school. His main interests include knowledge-based instructional systems and human—computer interaction. Richer is a member of the IEEE, ACM, SigChi, and AAAI.)