Results


Seventh Workshop on the Validation and Verification of Knowledge-Based Systems

AI Magazine

The annual Workshop on the Validation and Verification of Knowledge-Based Systems is the leading forum for presenting research on the validation and verification of knowledge-based systems (KBSs). The 1994 workshop was significant in that there was a definitive move in the philosophical position of the workshop from a testing-and toolbased approach to KBS evaluation to that of a formal specification-based approach. This workshop included 12 full papers and 5 short papers and was attended by 35 researchers from government, industry, and academia. The workshop is the leading forum for presenting research on the validation and verification of knowledge-based systems (KBSs). It has influenced the evolution of the discipline from its origins in 1988; at this time, researchers were asking the questions, How can we evaluate the correctness of KBS? How is this process different from conventional system evolution?


The Logic of Knowledge Bases A Review

AI Magazine

Hence, at a coarse-grained level of abstraction, KB-Ss can be characterized in terms of two components: (1) a knowledge base, encoding the knowledge embodied by the system, and (2) a reasoning engine, which is able to query the knowledge base, infer or acquire knowledge from external sources, and add new knowledge to the knowledge base. A knowledge-level account of a KBS (that is, a competencecentered, implementation-independent description of a system), such as Clancey's (1985) analysis of first-generation rule-based systems, focuses on the task-centered competence of the system; that is, it addresses issues such as what kind of problems the KBS is designed to tackle, what reasoning methods it uses, and what knowledge it requires. In contrast with task-centered analyses, Levesque and Lakemeyer focus on the competence of the knowledge base rather than that of the whole system. Hence, their notion of competence is a task-independent one: It is the "abstract state of knowledge" (p. This is an interesting assumption, which the "proceduralists" in the AI community might object to: According to the procedural viewpoint of knowledge representation, the knowledge modeled in an application, its representation, and the associated knowledge-retrieval mechanisms have to be engineered as As a result, they would argue, it is not possible to discuss the knowledge of a system independently of the task context in which the system is meant to operate.


Book Review

AI Magazine

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.


Book Reviews

AI Magazine

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.


Research Workshop on Expert Judgment, Human Error, and Intelligent Systems

AI Magazine

This workshop brought together 20 computer scientists, psychologists, and human-computer interaction (HCI) researchers to exchange results and views on human error and judgment bias. Human error is typically studied when operators undertake actions, but judgment bias is an issue in thinking rather than acting. Both topics are generally ignored by the HCI community, which is interested in designs that eliminate human error and bias tendencies. As a result, almost no one at the workshop had met before, and the discussion for most participants was novel and lively. Many areas of previously unexamined overlap were identified.


Letters

AI Magazine

Although they then cite a "slow, rigorous proof" by K. Hornik et al. that implies the superiority of neural systems to digital ones, the contrast needs to be reemphasized. In practice, since neural nets and Turing-equivalent systems are simulated on systems constructed from digital integrated circuits, they are of course equivalent. However, in theory, the fundamental computations of neural networks depend on the arithmetic of real numbers rather than integers. The ideal neural unit computes in a noisefree, infinite precision fashion. These computations can be simulated arbitrarily closely by a Turing machine, yet as the Greek philosopher Zeno observed 2200 years ago, the continuous computation can attain values in a fixed time that the digital approximation with uniform timestep will take infinite time to reach.



Book Reviews

AI Magazine

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.


Verification and Validation of Knowledge-Based Systems

AI Magazine

To give an integrated view of current research issues in this field, we organized this article along thematic lines, unifying the reports of the two separate meetings. Our report focuses on the trends that we think will be important in the near future in this field. The 1997 edition of EUROVAV was already the fourth time that the symposium was held. It was chaired by Jan Vanthienen (University of Leuven, Belgium) and Frank van Harmelen (Vrije Universiteit, Amsterdam) and held in the beautiful city of Leuven, Belgium. With 25 submissions (of which 16 were accepted) and 35 attendants, EUROVAV'97 was roughly the same size as other recent meetings.


Articles

AI Magazine

An expert system used in the control room of this blast furnace controls fluctuations in furnace temperature, thereby saving significant amounts of energy and costs. Representatives of universities and businesses were chosen by the Japan Technology Evaluation Center to investigate the state of the technology in Japan relative to the United States. The panel's report focused on applications, tools, and research and development in universities and industry and on major national projects. JTEC formed a panel of individuals from the academic and business communities to conduct this study. The primary objectives of the JTEC panel were to investigate Japanese knowledge-based systems development from both technological and business perspectives and compare progress and trends with similar developments in the United States. The panel focused on (1) applications in the business sector, (2) infrastructure and tools, (3) advanced knowledge systems development in industry, (4) advanced knowledge systems research in universities, and (5) national projects. The JTEC panel visited 19 sites during its 1-week visit to Japan in March 1992 and conferred with Japanese computer scientists and business executives both before and after the official visits. The panel visited four major computer manufacturers; eight companies that are applying expert systems to their operations; three universities; three national projects; and Nikkei AI, a publication that conducts an annual survey of expert system applications in Japan. This article summarizes the findings of the panel in each of the five areas listed. The panel members were Edward Feigenbaum, Stanford University (chair); Peter Friedland, National Aeronautics and Space Administration; Bruce B. Johnson, Andersen Consulting; H. Penny Nii, Stanford; Herbert Schorr, University of Southern California; and Howard Shrobe, Massachusetts Institute of Technology and Symbolics, Inc.). Robert Engelmore served as an ex officio member of the panel with the responsibility of producing the final report. Also present on the site visits were Y. T. Chien, National Science Foundation, and R. D. Shelton, JTEC. The sponsors of the JTEC study defined the dimensions of the study to include the following areas: (1) business-sector applications of expert systems; (2) advanced knowledgebased systems in industry; (3) advanced knowledge-based systems research in universities; (4) work at government laboratories, especially the laboratory of the Japanese Fifth-Generation Computer Project; and (5) the electronic dictionary research knowledge base building effort. The panel was also asked to observe the fuzzy system work being done in Japan, any neural network applications that affect expert system development, and the new national project known as Real-World Computing.