VT: An Expert Elevator Designer That Uses Knowledge-Based Backtracking

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.

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 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.

Presented is a discussion of several issues raised during the workshop sponsored by the Association for the Advancement of Artificial Intelligence on Coupling Symbolic and Numeric Computing in Expert Systems, which was held on 27 to 29 August 1987 in Seattle, Washington. Issues include the definition of coupled systems, motivations for coupling, coupled system architectures, and key factors in the design of coupled systems.

The 1987 Workshop on Distributed Artificial Intelligence (DAI) was held at Sea Ranch, California, 3 to 6 December 1987. Twenty-eight participants gathered in this rugged, windswept northern California coastal village to debate the theory and practice of DAI.

The first step in the development of an expert system is the extraction and characterization of the knowledge and skills of an expert. This step is widely regarded as the major bottleneck in the system development process. To assist knowledge engineers and others who might be interested in the development of an expert system, I offer (1) a working classification of methods for extracting an expert's knowledge, (2) some ideas about the types of data that the methods yield, and (3) a set of criteria by which the methods can be compared relative to the needs of the system developer. The discussion highlights certain issues, including the contrast between the empirical approach taken by experimental psychologists and the formalism-oriented approach that is generally taken by cognitive scientists.

As a book about search, it is thorough, at the state of the art, and contains expositions that will delight the expert with their clarity and depth. However, it is not, per se, a book about AI (nor was it intended to be) or about the history, philosophy, or cognitive aspects of heuristic knowledge.

Essentially a survey of the development of PC-based expert systems and a review of existing applications, languages, and shells, this book leaves many of the important questions unanswered. Essentially a survey of the development of PC-based expert systems and a review of existing applications, languages, and shells, this book leaves many of the important questions unanswered.