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An Assessment of Tools for Building Large Knowledge-Based Systems

AI Magazine

A number of tools that support the development, execution, and maintenance of knowledge-based systems are marketed commercially. Many of these tools, however, are designed for applications that can be executed on personal computers and are not suitable for building large knowledge-based systems. The market for knowledge engineering tools designed for applications that require the computational power of a Lisp machine or an engineering workstation is dominated by a few vendors. This article is an assessment of the current state of tools used to build large knowledge-based systems. This assessment is based on the collective strengths and weaknesses of several tools that have been evaluated. In addition, an estimate is made of the features that will be required in the next generation of tools.


The Yale Artificial Intelligence Project: A Brief History

AI Magazine

In the restaurant script, notated as $RESTAURANT, the roles might directly to the United Press International Yale researchers explored intentionality include customer, waitress, and cook; news wire and could skim news One of the earliest programs to the props could be a menu, table, and stories in dozens of different domains, embody goals and plans within the silverware; the locations could be the and produce summaries in several languages. CD paradigm was Jim Meehan's bar, dining area, and kitchen; and the On the DEC-20 (which by TALESPIN, which made up stories events would include arriving, seating, 1978 had replaced the PDP-101, similar to the fables of Aesop.


A Graduate Level Expert Systems Course

AI Magazine

This article presents an approach to a graduate-level course in expert, knowledge-based, problem-solving systems. The core of the course, and this article, is a set of questions called a profile, that can be used to characterize and compare each system studied.


Ecclesiastes: A Report from the Battlefields of the Mind-Body Problem

AI Magazine

One observer's report on the Artificial Intelligence and Human Mind Conference, held 1-3 March at Yale University. The conference was organized and sponsored by Truth ( a journal of modern thought) and The International Institute for Mankind. The conference included Sir John Eccles, the nobel laureate neurobiologist, physicists Henry Margenau and Eugene Wigner, and AI researchers Marvin Minsky, Michael Arbib, Hans Moravec and Doug Lenat.




Ecclesiastes: A Report from the Battlefields of the Mind-Body Problem

AI Magazine

One observer's report on the Artificial Intelligence and Human Mind Conference, held 1-3 March at Yale University. The conference was organized and sponsored by Truth ( a journal of modern thought) and The International Institute for Mankind. The conference included Sir John Eccles, the nobel laureate neurobiologist, physicists Henry Margenau and Eugene Wigner, and AI researchers Marvin Minsky, Michael Arbib, Hans Moravec and Doug Lenat.


Report on the 1986 Artificial Intelligence and Simulation Workshop

AI Magazine

MA 02115 A Public Service of This Publicaiion 0 1987 National Commission for Cooperative Education page must specify exactly one topic ence proceedings. At most one addi-Please send program suggestions from the above list of topics (as well tional page can be used, at a cost to and inquiries to: as a subtopic, if applicable) as the the authors of $250 Papers exceeding Reid G. Smith main topic of the paper. This information six pages, and papers violating the Schlumberger Palo Alto Research helps determine which members instructions to authors, will not be 3340 Hillview Ave. of the program committee review included in the proceedings.


AAAI News

AI Magazine

Furniture, fixtures and equipment are stated word processing program.


Thinking Backward for Knowledge Acquisition

AI Magazine

This article examines the direction in which knowledge bases are constructed for diagnosis and decision making. When building an expert system, it is traditional to elicit knowledge from an expert in the direction in which the knowledge is to be applied, namely, from observable evidence toward unobservable hypotheses. However, experts usually find it simpler to reason in the opposite direction-from hypotheses to unobservable evidence-because this direction reflects causal relationships. Therefore, we argue that a knowledge base be constructed following the expert's natural reasoning direction, and then reverse the direction for use. This choice of representation direction facilitates knowledge acquisition in deterministic domains and is essential when a problem involves uncertainty. We illustrate this concept with influence diagrams, a methodology for graphically representing a joint probability distribution. Influence diagrams provide a practical means by which an expert can characterize the qualitative and quantitative relationships among evidence and hypotheses in the apporiate direction. Once constructed, the relationships can easily be reserved into the less intuitive direction in order to perform inference inference and diagnosis. In this way, knowledge acquisition is made cognitively simple; the machine carries the burden of translating the representation.