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In my view, the present "critical situation" in M.T., is not due to the fact that genuine Mechanical Translation is inherently impossible, as Bar-Hillel thinks, but to the fact that the mechanizable techniques at present being used to analyse language are not powerful enough to detect the message, or argument, of any particular text. Other papers from this conference online. See Table of Contents with links to online papers from the Proc. 1961 International Conference on Machine Translation of Languages and Applied Language Analysis (http://www.mt-archive.info/NPL-1961-TOC.htm). Proc. 1961 International Conference on Machine Translation of Languages and Applied Language Analysis, pp. 438-475, London: Her Majesty's Stationery Office, 1962.

Technical Report, Panoramic Research, Inc, Palo Alto, CA

Englewood Cliffs, N.J.: Prentice Hall

In Self-Organizing Systems 1962, pp 435–461.

CACM, 5, 394–397

This paper describes an attempt to make use of machine learning or self-organizing processes in the design of a pattern-recognition program. The program starts not only without any knowledge of specific patterns to be input, but also without any operators for processing inputs. Operators are generated and refined by the program itself as a function of the problem space and of its own successes and failures in dealing with the problem space. Not only does the program learn information about different patterns, it also learns or constructs, in part at least, a secondary code appropriate for the analysis of the particular set of patterns input to it.

MH-1 is a motorized and sensitized servomanipulator operated by the TX-O computer at the Massachusetts Institute of Technology. It serves as an experimental vehicle to explore the feasibility of direct relations between a digital computer and the physical world with which this computer is concerned. Usually, a human interpreter stands between the computer and the physical world. Instead, the TX-O computer in the MH-1 system is programmed to perform by itself some of the functions normally assigned to the human intermediary; namely, to perceive the world, to appreciate it, and to determine a reasonable course of action after a goal has been specified for the hand. The data processing tools used are, rather than numerical operations on quantitative signals, pattern recognition and simulation of higher cognitive processes such as awareness and understanding. This paper describes some of the experiments performed with MH-1 and the mechanisms upon which the capabilities of MH-1 are based.

The purpose of this report is to describe in detail an informationProcessing model of elementary human symbolic learning processes. Thismodel is realized by a computer program called the Elementary Perceiverand Memorizer (EPAM).The EPAM program is the precise statement of an information processingtheory of verbal learning that provides an alternative to other verballearning theories which have been proposed.1 It is the result of an attemptto state quite precisely a parsimonious and plausible mechanism sufficientto account for the rote learning of nonsense syllables. The criticalevaluation of EPAM must ultimately depend not upon the interest whichit may have as a learning machine, but upon its ability to explain andPredict the phenomena of verbal learning. Proceedings of the Western Joint Computer Conference, 1961, 19:121-132. Reprinted in Feigenbaum & Feldman, Computers and Thought (1963).

Artificial intelligence project memo 30, Massachusetts Institute of Technology.