The first Artificial Intelligence (AI) and simulation workshop was held during the National Conference on Artificial Intelligence (AAAI-86) on 11 August 1986 at Wharton Hall, the University of Pennsylvania.

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.

This report contains a historical perspective on previous Distributed Artificial Intelligence Workshops, highlights of the roundtable discussions, and a collection of research abstracts submitted by the participants.

The questions of how humans process uncertain information is important to the development of knowledge-based systems in term of both knowledge acquisition and knowledge representation. This article reviews three bodies of psychological research that address this question: human perception, human probabilistic and statistical judgement, and human choice behavior. The general conclusion is that human behavior under certainty is often suboptimal and sometimes even fallacious. The requirements for a system designed to reduce the effects of human factors in the processing of uncertain knowledge are introduced.

The First International Workshop on User Modeling in Natural Language Dialogue Systems was held 30-31 August 1986 in Maria Laach, West Germany. Issues addressed by the participants included the appropriate contents of a user model, techniques for constructing user models in both understanding and generating natural language dialogue, and the development of general user-modeling systems. This article includes an overview of the presentations made at the workshop. It is a compilation of the author's impressions and observations and is, therefore, undoubtedly incomplete; and at times might fail to accurately represent the views of the researcher presenting the work.

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.

Krasner is the author of Department of Neurology at the University the "CSCW '86 Summary Report." of California at Davis.

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.

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.

Furniture, fixtures and equipment are stated word processing program.