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First International Workshop on User Modeling
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.
Report on the First National Conference on Knowledge Representation and Inference in Sanskrit
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.
Viewing the History of Science as Compiled Hindsight
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.
AAAI News
Ms. Claudia Mazzetti AAAI AAAI has supported small workshops for the last several years. This support has 445 Burgess Drive included publicity, printing, office help, and subsidies for other expenses. Any topic in AI science or technology is appropriate, and anyone may volunteer Submit all proposals to: to organize a workshop on any topic. The organizer(s) should determine Jay M. Tenenbaum, Chair, AAAI Conference the topic, the date, the site, and the procedure for selecting papers and attendees. Committee He or she should also decide whether preprints should be distributed.
Contributors
Tin Nguyen performed the work contained in the article "Knowledge Base Verification" while at Lockheed and is currently working for Bell Northern Research as a member of the research Deanne Pecora, a staff engineer with the Lockheed Artificial Intelligence Center, 2710 Sand Hill Road, Menlo Park, California 94025, is working on Rick Briggs, author of "Knowledge Representation and Inference in Sanskrit: A applying knowledge-based systems to Review of the First National Conference," is a senior engineer at Delfin Systems, real problems. She is a coauthor of 1349 Moffett Park Drive, Sunnyvale, California 94089. Briggs is currently working "Knowledge Base Verification." Walt Perkins, coauthor of IIKnowledge Base Verification" is a consulting scientist Lindley Darden, who wrote "Viewing the History of Science as Compiled Hindsight,lI with the Lockheed Artificial is an associate professor in the departments of philosophy and history and InteIligence Center, 2710 Sand Hill a member of the graduate faculty in the Committee on the History and Philosophy Road, Menlo Park, California 94025 of Science at the University of Maryland, College Park. She is currently and the principal developer of the serving in the second year of a halftime research appointment at the University Lockheed expert system. of Maryland Institute for Advanced Computer Studies.
Coupling Symbolic and Numerical Computing in Knowledge-Based Systems
Kitzmiller, C. T., Kowalski, Janusz . S
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.
The Problem of Extracting the Knowledge of Experts from the Perspective of Experimental Psychology
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.
Artificial Intelligence Research in Australia -- A Profile
Smith, Elizabeth, Whitelaw, John
Does the United States have a 51st state called Australia? A superficial look at the artificial intelligence (AI) research being done here could give that impression. A look beneath the surface, though, indicates some fundamental differences and reveals a dynamic and rapidly expanding AI community. 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. What we have seen as result is not an incremental creep of AI awareness in Australia but a quantum leap with significant industry and government support. The first systematic study of the Australian AI effort was undertaken by the Australian Department of Science (DOS) in 1986. The study took as its base the long-running research report Artificial Intelligence in Australia (AIIA), produced by John Debenham (1986). The picture that emerged is interesting. AI researchers are well qualified, undertaking research at the leading edge in their fields, and have significant potential to develop further. The results of this study were published by DOS in the Handbook of Research and Researchers in Artificial Intelligence in Australia (Department of Science1986). This article is based on key findings from the study and on additional information gained through meeting and talking with researchers and research groups.