We describe a program for verifying that a set of rules in an expert system comprehensively spans the knowledge of a specialized domain. The program has been devised and tested within the context of the ONCOCIN System, a rule-based consultant for clinical oncology. The stylized format of ONCOIN's rule has allowed the automatic detection of a number of common errors as the knowledge base has been developed. This capability suggests a general mechanism for correcting many problems with knowledge base completeness and consistency before they can cause performance errors.

Today, surrounded by so many automatic machines industrial robots, and the R2-D2's of Star wars movies, most people think AI is much more advanced than it is. But still, many "computer experts" don't believe that machines will ever "really think." I think those specialists are too used to explaining that there's nothing inside computers but little electric currents. And there are many other reasons why so many experts still maintain that machines can never be creative, intuitive, or emotional, and will never really think, believe, or understand anything.

In Memoriam: John G. Gaschnig

Work on expert systems has received extensive attention recently, prompting growing interest in a range of environments. Much has been made of the basic concept and of the rule-based system approach typically used to construct the programs. Perhaps this is a good time then to review what we know, asses the current prospects, and suggest directions appropriate for the next steps of basic research. I'd like to do that today, and propose to do it by taking you on a journey of sorts, a metaphorical trip through the State of the Art of Expert Systems.

It appears, however, that we [in AI] are now (finally!) on the verge of practicality in a number of specialities within machine intelligence more or less simultaneously. This can be expected to result in the short term in a qualitative shift in the nature of the field itself, and to result in the longer term in a shift in the way certain industries go about their businessThis paper will discuss three specific areas of work in machine intelligence that MIC [Machine Intelligence Corporation] feels are ripe for commercial application: machine vision, naturallanguage access to computers, and expert systems. It will close with some observations on what makes these areas appropriate for application at this time, and on the difference between a technical solution to a problem and a product.In Hayes, J. E., Michie, D., and Pao, Y.-H. (Eds.), Machine Intelligence 10. Ellis Horwood.

Advanced Information and Decision Systems (AI-DS) is a relatively new, employee-owned company that does basic and applied research, product development, and consulting in the fields of artificial intelligence, computer science, decision analysis, operations research, control theory, estimation theory, and signal processing. AI&DS performs studies, analyses, systems design and evaluation, and software development for a variety of industrial clients and government agencies, including the Department of Defense and Energy.

Carnegie-Mellon University has established a Robotics Institute to bring its expertise in engineering, science, and industrial administration to bear upon the problem of national industrial productivity. The institute has been established to undertake advanced research and development in seeing, thinking robots and intelligent systems, and to facilitate transfer of this technology to industry. The Institute is engaged in broad programs of research in robotics, artificial intelligence, manufacturing technology, micro-electronics technology, and computer science. The Institute offers the promise of dramatic advances that will not only improve the productivity of all types of employees but also lead to improvements in the "quality of life" for all.

R1 is a rule-based program that configures VAX-11 computer systems. Given a customer's purchase order, it determines what, if any, substitutions and additions have to be made to the order to make it consistent and complete and produces a number of diagrams showing the spatial and logical relationships among the 90 or so components that typically constitute a system. The program has been used on a regular basis by Digital Equipment Corporation's manufacturing organization since January of 1980. R1 has sufficient knowledge of the configuration domain and of the percliarities of the various configuration constraints that at each step in the configuration process, it simply recognizes what to do; thus it requires little search in order to configure a computer system.

By-Laws of the Association for the Advancement of Artificial Intelligence

The Robotics Project (the "Hand-Eye Project") evolved within the Stanford Artificial Intelligence Laboratory under the guidance of John McCarthy, Les Earnest, Jerry Feldman, and Tom Binford. Major efforts have been undertaken to isolate and solve fundamental problems in computer vision, manipulation, and autonomous vehicles. Stereo vision and texture have been examined. Several generations of robot programming languages have resulted in AL, an intermediate-level language for commanding manipulation.