The system has reduced time The system, developed by Stereo-spent by store personnel on the telephone seeking answers to point-of-sale Graphics (San Rafael, Calif.), uses a technical problems, and it allows the help desk analysts to handle a wider range video projector equipped with a of responsibilities for the company. Viewers wear passive eye Swedish stock exchange, has developed an intelligent system to advise on how wear which allows each eye to view to deal in stocks and shares. The company's "hit rate" of dealing correctly with the appropriate image, thereby providing stocks has reportedly increased from 60% to 90%. IntelliCorp Inc. (Mountain View, Calif.), an expert system vendor, and James Inference Corp. (El Segundo, Calif.), Martin & Co. (Reston, Va.), a computer-aided software engineering (CASE) consulting a supplier of expert system development group, have launched a field test program for an object-oriented information tools, has teamed up with IDS engineering environment. The new product, called Object Management Financial Services (Minneapolis, Workbench, directly supports rapid application development, and will either Minn.) to jointly develop Macintosh generate a system immediately or draw information from currently available versions of Inference products.

In VISION-21 Symposium. NASA Lewis Research Center and the Ohio Aerospace Institute.

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Vision based mobile robot guidance has proven difficult for classical machine vision methods because of the diversity and real time constraints inherent in the task. This thesis describes a connectionist system called ALVINN (Autonomous Land Vehicle In a Neural Network) that overcomes these difficulties. ALVINN learns to guide mobile robots using the back-propagation training algorithm. Because of its ability to learn from example, ALVINN can adapt to new situations and therefore cope with the diversity of the autonomous navigation task. But real world problems like vision based mobile robot guidance presents a different set of challenges for the connectionist paradigm.

The purpose of the Institute of Mathematical Statistics (IMS) is to foster the development and dissemination of the theory and applications of statistics and probability. The Institute was formed at a meeting of interested persons on September 12, 1935, in Ann Arbor, Michigan, as a consequence of the feeling that the theory of statistics would be advanced by the formation of an organization of those persons especially interested in the mathematical aspects of the subject. The Annals of Statistics and The Annals of Probability (which supersede The Annals of Mathematical Statistics), Statistical Science, and The Annals of Applied Probability are the scientific journals of the Institute. These and The IMS Bulletin comprise the official journals of the Institute. The Institute has individual membership and organizational membership.

The field of AI is directed at the fundamental problem of how the mind works; its approach, among other things, is to try to simulate its working -- in bits and pieces. History shows us that mankind has been trying to do this for certainly hundreds of years, but the blooming of current computer technology has sparked an explosion in the research we can now do. The center of AI is the wonderful capacity we call learning, which the field is paying increasing attention to. Learning is difficult and easy, complicated and simple, and most research doesn't look at many aspects of its complexity. However, we in the AI field are starting. Let us now celebrate the efforts of our forebears and rejoice in our own efforts, so that our successors can thrive in their research. This article is the substance, edited and adapted, of the keynote address given at the 1992 annual meeting of the Association for the Advancement of Artificial Intelligence on 14 July in San Jose, California. AI Magazine 14(2): 36-48.

Artificial Intelligence, 62 (2), 303-39.

In AAAI-93, pp. 811–816.

In AAAI-93, pp. 676–682. In german, P. Z. Panini–Backus form suggested. CACM, 10. (3), 137

In AAAI-93, pp. 724–730.