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 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.

Hand's book is well written and well researched. The author has taken great care in presenting previous work in detail and has quoted the erlier literature when applicable. Nevertheless, the book fails in two respects.

The conference was inspired by an article that appeared in the Spring 1987 issue of AI Magazine -- "Knowledge Representation in Sanskrit and Artificial Intelligence." A working group has been created to pursue the goals of the conference and to possibly arrange another conference for 1987 and 1988.

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.

This article is a written version of an invited talk on artificial intelligence (AI) and the history of science that was presented at the Fifth National Conference on Artificial Intelligence (AAAI-86) in Philadelphia on 13 August 1986. Included is an expanded section on the concept of an abstraction in AI; this section responds to issues that were raised in the discussion which followed the oral presentation. The main point here is that the history of science can be used as a source for constructing abstract theory types to aid in solving recurring problem types. Two theory types that aid in forming hypotheses to solve adaptation problems are discussed: selection theories and instructive theories. Providing cases from which to construct theory types is one way in which to view the history of science as "complied hindsight" and might prove useful to those in AI concerned with scientific knowledge and reasoning.

This conference is analogous to the ancient texts but little procedural consultation of philosophers and cognitive information), we had to rely on the This report is a review of the First psychologists by computer scientists pandits to whom the oral tradition had National Conference on Knowledge in the beginnings of AI. been passed. Representation and Inference in Western psychology and philosophy is The conference was inspired by Sri Sanskrit, Bangalore, India, 20 through quite different from the Indo-Aryan Paramananda Bharathi Swamiji and 22 December, 1986 The conference tradition: the former has its basis in was organized by Dr. H. N. Mahabala was inspired by an article that Aristotelian logic and the scientific (president, Computer Society of India; appeared in the Spring 1985 issue of method, whereas the latter is also chairman, Indian Institute of AI Magazine--"Knowledge based on introspection and internal Technology) and others. The conference Representation in Sanskrit and experience Nevertheless, both these was attended by the vice-chairman Artificial Intelligence." Virtually text.The purpose of AI in this context every institute of science, mathematics is to derive a "method" for natural language and engineering was represented. A working group has been created to was implicit; it was not the focus.

Even though sues raised during the workshop sponsored emerged during the workshop. In many situations, users are not sufficiently defined or Seattle, Washington. Issues include the need guidance and counseling in order understood to be amenable to traditional definition of coupled systems, motivations to solve the problem at hand. In control system--one that combines such situations, users often need help techniques from artificial intelligence in determining which specific algorithm (AI), control theory, and operations or technique should be research (Kowalik et al. 1986). In other situations, traditional techniques to perform the need is more basic--for guidance in many routine tasks, sophisticated determining whether the problem at hand can be solved and, if so, whether techniques are needed to handle many the resources that can be brought to of the humanlike functions.