Even least commitment systems such as MOLGEN (Stefik 1981a, 1981b) are sometimes forced to guess. In the course of designing genetics experiments, MOL-GEN tries to avoid making a decision until all constraints that might affect the decision are known. In some cases, this postponement is not possible, and the system becomes stuck; none of the pending decisions can be made with complete confidence. In such a case, a decision based on partial information is needed, and such a decision might be wrong. In this case, a problem solver needs the ability either to backtrack to correct bad decisions or to maintain parallel solutions corresponding to the alternatives at the stuck decision point However, if alternative guesses exist at each point, and there are many such decision points on each solution path, a commitment to examine every possible combination of alternatives proves unwieldy.

VT (vertical transportation) is an expert system for handling the design of elevator systems that is currently in use at Westinghouse Elevator Company. Although VT tries to postpone each decision in creating a design until all information that constrains the decision is known, for many decisions this postponement is not possible. In these cases, VT uses the strategy of constructing a plausible approximation and successively refining it. VT uses domain-specific knowledge to guide its backtracking search for successful refinements. The VT architecture provides the basis for a knowledge representation that is used by SALT, an automated knowledge-acquisition tool.

MetLife processes over 260,000 life insurance applications a year. Underwriting of these applications is labor intensive. Automation is difficult because the applications include many free-form text fields. The application contains questions that can be answered by structured data fields (yes-no or pick lists) as well as questions that require free-form textual answers. Currently, MetLife's Individual Business Personal Insurance unit employs over 120 underwriters and processes in excess of 260,000 life insurance applications a year.

Studies in design methodology provide various structured approaches to the design process. Many books provide definitions and elaborations of the design process: In the structural engineering field, such books include Holgate (1986) and Lin and Stotesbury (1981). More generally, various design methods and techniques are described in Alexander (1964) and Jones (1970). These design methods share the characteristic of prescribing a general set of tasks to be performed by the designer. One problem with design methodologies is that such approaches prescribe what a designer should do but not how.

The system described in this article is currently working in the field at the Sales Department of EKATO, one of the world's most successful manufacturers of industrial mixing machines. It was developed in close cooperation with the Fraunhofer Institute for Information and Data Processing (IITB) during a three-year period. Industrial mixing machines, better known as agitators, are widely used in industrial manufacturing. They are especially useful for the chemical and pharmaceutical industries, food production, and biotechnology. The basic structure of an industrial agitator is shown in figure 1.

Currently in the United States, it is estimated to infect 3 to 5 million persons, is the leading cause of death in adults from 14 to 35, and is the nation's leading cause of productive years of life lost aggregated over all age groups. HIV is estimated to infect 40 to 50 million persons worldwide (CDC 1997). The high rate of HIV viral mutation both makes development of a vaccine difficult and results in rapid positive selection for drug-resistant mutant strains. Recent multidrug combination therapies are encouraging but in most cases ultimately fail because of the development of drug resistance (O'Brian et al. 1996). A general theory of HIV drug resistance still is not in hand, but a number of specific sequence mutations in the HIV genome have been described in the scientific literature and associated with increased resistance to certain drugs.

Moreover, the system was designed from the beginning to be maintained on an ongoing basis without the involvement of senior knowledge engineers. In the manufacture of paper, wood is first pulped to separate its fibers. One of the predominant pulp processes is done in a kraft pulp mill and consists of cooking wood chips at elevated temperature and pressure in the presence of certain chemicals (alkali and sulfide), washing the resultant brown pulp, bleaching to make the pulp white, and drying the pulp for shipment to a paper mill. Pitch, or wood resin, is the material in wood that is insoluble in water but soluble in organic solvents. It usually makes up 14 percent of the weight of wood after the bark is removed and is often a sticky material.

In fact, we have a knowledge infrastructure already, and it is already immense. AI Mugaztine 7(l): 34- served the most successful work on expert systems: that (today) knowledge comes (mostly) from people. Editor: Mark Stefik Xerox PARC 3333 Coyote Hill Road Palo Alto, California 94304 Workshop on the Foundations of Al: An On-The-Spot Report The NSF and AAAI sponsored Workshop on the Foundations of AI (6-8 February 1986, Las Cruces, New Mexico) is over and, from my perspective at least, it was a very worthwhile event. I am preparing a report that I will send to you in due course. In addition, I noticed that John McCarthy was snapping freely with his camera at the workshop.

As a system scientist doing modeling and simulation, I have been interested for some time in ways that modeling and simulation and AI could be of value to each other. After all, both areas have their roots in putting knowledge into useful representations. I have speculated (AI Magazine, summer 1989, pp. With respect to breadth of coverage and potential readership, Artificial Intelligence, Simulation, and Modeling does provide a broad survey of current research, but it is written from an AI perspective and will find a greater readership among AI researchers than simulationists. Mark E. Lacy is manager of computational The cover to Expert Systems in Business: A Practical Approach by Michael L. Barrett and Annabel C. Beerel (Ellis Horwood Limited, Chichester, England, 1988, 259 pages, $36.95, ISBN O-7458-0269-9) contains an abstract design in colors of violet, brilliant green, and dark magenta.

Teknowledge, Inc. Palo Alto, CA 9&'01 Over the past few years, the character of the AI community has changed. Artificial intelligence is not in itself a commercial field, but a science and a technology As an academic discipline, it is a collection of concepts and ideas which are appropriate for rcscarch, but which cannot be marketed. However, artificial intelligence is the scientific foundation for several growing commercial technologies The three most important are robotics and vision (which for simplicity's sake I will consider as one field), natural language processing, and knowledge engineering. Supporting markets are forming which will provide hardware and software tools for use in these three areas. The potential value of Artificial Intelligence can be bctter understood by contrasting it with natural intelligence.