If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
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.
This article discusses several effective techniques for expert system knowledge acquisition based on the techniques that were successfully used to develop the Central Office Maintenance Printout Analysis and Suggestion System (COMPASS). Knowledge acquisition is not a science, and expert system developers and experts must tailor their methodologies to fit their situation and the people involved. Developers of future expert systems should find a description of proven knowledge-acquisition techniques and an account of the experience of the COMPASS project in applying these techniques to be useful in developing their own knowledge-acquisition procedures.
A superficial look at the artificial intelligence (AI) research being done here could give that impression. General awareness of the Australian AI research community has been growing slowly for some time. AI was once considered a bit esoteric -- the domain of an almost lunatic fringe- but the large government -backed programs overseas, as well as an appreciation of the significance of AI products and potential impact on the community, have led to a reassessment of this image and to concerted attempt to discover how Australia is to contribute to the world AI research effort and hoe the country is to benefit from it. The results of this study were published by DOS in the Handbook of Research and Researchers in Artificial Intelligence in Australia (Department of Science1986).
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.