The project is large and has a number of components that have been documented at length. These components have never been drawn together in one document; thus, this article describes the project and gives a taste of the individual subprojects that have kept the project members so busy for so long. A large number of publications have emerged from the project, so a full bibliography of the work appears for the reader who wants to follow up on any intriguing topics. AAP straddles a number of research areas and, thus, does not fall easily into any one sphere of interest. A certain amount of work has been done on the parallelizing of expert systems, most notably by Gupta (1986).

The annual conference of the American Association for Artificial Intelligence (AAAI) is the premier U.S. gathering for artificial intelligence (AI) theoreticians and practitioners. Regardless of the exact figure, I believe that the majority of large U.S. organizations are currently preparing to put AI technology into operation or have already done so. IBM Unveils Its Al Plans As if to testify that AI is now legitimate technology in corporate America, IBM chose AAAI-86 to unfurl its dedication to AI. In the keynote address, Herb Schorr, IBM's AI czar, presented IBM's recently organized program for AI activities. Schorr leads IBM's AI Project Office, a new type of IBM organization that will permeate all IBM activities and organizations related to AI. Schorr's organization currently consists of 12 people with full responsibility within IBM for (1) developing AI products for internal and external use, (2) marketing AI products outside IBM, and (3) applying AI tools and technology within IBM.

"It was good to see the number of student attendees up," noted American Association for Artificial Intelligence (AAAI) President Tom Mitchell, "and that our attendance was so high despite the economic downturn. I think the meeting was even more stimulating because of the co-location of AAAI with so many other conferences in Edmonton at the same time." This article provides a few snapshots of the vast and varied content of the 2002 conferences. Proceedings of AAAI-02 and IAAI-02 are available from AAAI Press (www.aaaipress.org). AAAI is grateful for the outstanding work of the conference committee members as well the support of the following organizations for this year's conference: Association of Computing Machinery SIGART, Alberta Informatics Circle of Research Excellence (iCORE), Defense Advanced Research Projects Agency (DARPA), NASA Ames Research Center, the National Science Foundation's Directorate for Computer and Information Science and Engineering (CISE), and the Naval Research Laboratory.

This article is a summary of the Workshop on Explanation held during the 1988 National Conference on Artificial Intelligence in St. Paul, Minnesota. The purpose of the workshop was to identify key research issues in the rapidly emerging area of expert system explanation. Expert system explanation is the study of how to give an expert system the ability to provide an explanation of its actions and conclusions to a variety of users (including the domain expert, knowledge engineer, and end user). The 1988 AAAI Workshop on Explanation brought together many of the world's experts on expert system explanation in an attempt to highlight key research areas and questions that should be the focus of subsequent work. The one-day workshop was organized into five sessions of short presentations, each followed by panelled open discussion among the 35 workshop participants.

"Over the last decade a new technology has begun to take hold in... business, one so new that its significance is still difficult to evaluate. While many aspects of this technology are uncertain, it seems clear that it will move into the managerial scene rapidly, with definite and far reaching impact on managerial organization." This article examines the near-term impact of expert system technology on work and the organization. First, an approach is taken for forecasting the likely extent of the diffusion, or success, of the technology. Next, the case of advanced manufacturing technologies and their effects is considered.

In reviewing a book of this kind, it is necessary to answer three questions: (1) how important is the workshop topic, (2) how valuable are the included papers, and (3) how coherent is the volume as a whole? I address each question in turn. In the last decade, knowledgebased systems (KBSs) emerged from being a research subfield within AI to become an application software technology. Although many specific aspects of knowledge acquisition, representation, and reasoning remained active research topics, the methods and tools required to build useful and powerful KBS applications had become sufficiently well understood to facilitate the development and delivery of systems in many diverse domains. However, as organizations began to use the technology, concerns arose about the reliability of KBSs.

Johanna Moore's work in the area of computer-generated explanation has been highly influential. Her thesis work, as well as the subsequent work of her and her students, has helped to change the way we think about the problem of generating explanations. The crux of the explanation problem, according to Moore, is not how to present information as such but how to impart an understanding on the user. The explanation system should be flexible enough that if an initial explanation fails to convey the understanding, it can try explaining the concept in a different way. The system should be aware of what it previously said to the user and what its communicative goals were at the time.

The two-volume set entitled Knowledge-Based Systems (Volume 1, Knowledge Acquisition for Knowledge-Based Systems, 355 pp., and Volume 2, Knowledge Acquisition Tools for Expert Systems, 343 pp., Academic Press, San Diego, California, 1988), edited by B. R. Gaines and J. H. Boose, is an excellent collection of papers useful to both commercial practitioners of knowledge-based-systems development and research-oriented scientists at specialized centers or academic institutions. The set is the result of a call for papers to support the first American Association for Artificial Intelligence Knowledge Acquisition for Knowledge-Based Systems Workshop, held 3-7 November 1986 in Banff, Canada. Although the conference was held three years ago, these volumes are still timely and sorely needed. Few books dedicated to knowledge acquisition exist. The first volume, Knowledge Acquisition for Knowledge-Based Systems, begins with a paper whose title sounds appropriate: "An Overview of Knowledge Acquisition and Transfer" by the editor B. R. Gaines.

Building Large Knowledge-Based Systems (Addison-Wesley, Reading, Massachusetts, 1990, 372 pages, $39.75, ISBN O-201-51752-3) by Douglas B. Lenat and R. V. Guha is an interim report on the Microelectronic and Computer Technology Corporation (MCC) Cyc project. Cyc is an ambitious lo-year effort whose goal is to overcome the brittleness of contemporary expert systems by capturing the millions of facts and heuristics that MCC researchers consider to be the consensus reality that all intelligent beings share and that leads to common sense. As the authors state in their preface, "There are deep, important issues that must be addressed if we are ever to have a large intelligent knowledge-based program: What ontological categories would make up an adequate set for carving up the universe? What are the important things most human beings today know about solid objects? This book does an admirable job of presenting their research.

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.