Technical report MIT/LCS/TR-340, Laboratory for Computer Science, MIT.

JACM, 32 (4), 755-61.

Proc. Workshop on Uncertainty and Probability in Artificial Intelligence, Los Angeles, CA, pages 9-20. Association for Uncertainty in Artificial Intelligence, Mountain View, CA, August 1985.

Informal note INCSLI-85-4, Center for the Study of Language and Information. Not available online. Alternative: Davies, Todd R.; Russell, Stuart J. A Logical Approach to Reasoning by Analogy. SRI International Technical Note 385, July 1987. Determination, uniformity, and relevance: Normative criteria for generalization and reasoning by analogy. In D. H. Helman (ed.), Analogical Reasoning, 227-250. Kluwer Academic Publishers, 1988.

Pitman.

Review of A Practical Guide to Designing Expert Systems

Letters to the Editor

The AI field needs major breakthroughs in its thinking to achieve continuous, sensory-gathered, machine learning from the environment on unlimited subjects. The way motivate such dramatic progress is to articulate and endorse research goals for machine behavior so ambitious that limited-domain, problemsolving knowledge representation methods are disqualified at the outset, thus forcing ourselves to produce valuable new "thoughtware." After exploring why the tendency to associate intelligence with problem-solving may be a mental roadblock to further progress in AI science, some preliminary thinking tools are introduced more suitable for sensory learning machine research. These include lifelong sensorimotor data streams, representation as a symbolic recording process, knowledge transmission, and the totality of knowledge.

This article describes one person's experience in coming from an academic environment to work at Digital Equipment Corporation. The author feels his own experience has paralleled the transfer of AI technology from academia to industry, where AI researchers must live up to very different expectations, but also enjoy very different rewards. This article covers the historical background of DEC's involvement with AI, the development of R1- known internally and henceforth in this article as XCON-and DEC's experiences with it and its consequences. Finally, the article offers advice for other corporations planning to develop their own capabilities in AI.

Jim Kornell, Robert Park, Christopher Dungan, Joop Schopman, David Drager, Nils J. Nilsson, Marty Kalin, John Gavin, Bernard Meltzer, Robert Salmansohn, Keith McCammon, Loren Martindale Abstract Subjects include AI's impact on employment, the AAAI conference, a response to McCarthy's Presidential Message, AI going public, and computerless expert systems. Subjects include AI's impact on employment, the AAAI conference, a response to McCarthy's Presidential Message, AI going public, and computerless expert systems.