The MITRE Corporation is a scientific and technical an acronym for Knowledge-Based System. Subsequently, organization engaged in system engineering activities, Rome Air Development Center took over support of the principally in support of the United States Air Force and project and continues to fund part of our AI research effort. MITRE is a special kind of engineering MITRE's current research is summarized below. The corporation is a Federal Contract Bedford center is supported by 15 Symbolics Lisp machines Research Center, a designation covering the handful netted to two Vax-780 file servers, while the Washington of independent institutions that perform governmentsponsored center is supported by both a classified and an unclassified research. It is an independent, nonprofit corporation facility, with 2 Lambdas and 2 Symbolics Lisp machines designed and m.anagcd to provide long-term assistance respectively netted to Vax-780 file servers.

Research in AI within the Computer Science Department at the University of California, Los Angeles is loosely composed of three interacting and cooperating groups: (1) the Artificial Intelligence Laboratory, at 3677 Boelter Hall, which is concerned mainly with natural language processing and cognitive modelling, (2) the Cognitive Systems Laboratory, at 4731 Boelter Hall, which studies the nature of search, logic programming, heuristics, and formal methods, and (3) the Robotics and Vision Laboratory, at 3532 Boelter Hall, where research concentrates on robot control in manufacturing, pattern recognition, and expert systems for real-time processing.

The fifth Distributed Artificial Intelligence Workshop was held at the Schlumberger-Doll Research Laboratory from October 14 to 17, 1984. It was attended by 20 participants from academic and industrial institutions. As in the past, this workshop was designed as an informal meeting. It included brief research reports from individual groups along with general discussion of questions of common interest. This report summarizes the general discussion and contains summaries of group presentations that have been contributed by individual speakers.

I want to discuss two aspects of technology transfer. It took a committee several years to come up automation. Then I want to give my two cents worth on with this. It has a lot of words and you can't understand AI as a business activity. Interestingly enough, so does My particular focus is on commercial AI, that is, products Europe. The United States is dead last in utilizing this that incorporate AI that are being sold for profit, as technology-most of which came out of U.S. industry and opposed to "practical" AI, in which AI is incorporated into AI labs. The definition we used at Machine Intelligence views Commercial AI products take the form of equipment, a robot as a computer system with a peripheral attached systems, or software. This forces a different view of a robot, a of demonstrated successes in artificial intelligence systemsmaybe view that is useful in actually thinking about applications.

A variety of proposals for preferred methodological approaches has been advanced in the recent artificial intelligence (AI) literature. Rather than advocating a particular approach, this article attempts to explain the apparent confusion of efforts in the field in terms of differences among underlying methodological perspectives held by practicing researchers. The article presents a review of such perspectives discussed in the existing literature and then considers a descriptive and relatively specific typology of these differing research perspectives. It is argued that researchers should make their methodological orientations explicit when communicating research results, to increase both the quality of research reports and their comprehensibility for other participants in the field. For a reader of the AI literature, an understanding of the various methodological perspectives will be of immediate benefit, giving a framework for understanding and evaluating research reports. In addition, explicit attention to methodological commitments might be a step towards providing a coherent intellectual structure that can be more easily assimilated by newcomers to the field.

The following article briefly describes the development of tools and knowledge in human history and states that these two phenomena co-exist only in intelligent tolls. It focuses on the productive merits of the past intelligent tools and discusses the social and biohuman). Moreover, since the human beings were unable to produce an intelligent tool capable of outperforming man as a tool, the tech nological basis of slavery continued to persist throughout history. The article then examines the current achievements of computer technology in producing intelligent tools. It argues that the production of intelligent tools makes it possible to bypass the social and natural limitations of all past intelligent tools. Once these tools outperform humans as intelligent tools, man will no longer be indispensable as a production tool. Consequently, the inception of these new tools eradicates the technological basis of the subjugation of man by man. This eradication may start a new civilization by effecting higher human intelligence, more economic wealth and greater socio-political freedom in man's future society.

The choice of implication as a representation for empirical associations and for deduction as a model of inference requires a mechanism extraneous to deduction to manage uncertainty associated with inference. Consequently, the interpretation of representations of uncertainty is unclear. Representativeness, or degree of fit, is proposed as an interpretation of degree of belief for classification tasks. The calculation of representativeness depends on the nature of the associations between evidence and conclusions. Patterns of associations are characterized as endorsements of conclusions. We discuss an expert system that uses endorsements to control the search for the most representative conclusion, given evidence.

Artificial Intelligence Research at the University of Michigan

The Artificial Intelligence in Medicine (AIM) Workshop has become a tradition. Meeting every year for the past nine years, it has been the forum where all the issues from basic research through applications to implementations have been discussed; it has also become a community building activity, bringing together researchers, medical practitioners, and government and industry sponsors of AIM activities.

On October 17-19 1984 a workshop on non-monotonic reasoning was held at Mohonk Mountain House, outside New Paltz, New York. The workshop was organized by Raymond Reiter and Bonnie Webber, and was sponsored by the Association for the Advancement of Artificial Intelligence.