Princeton University Press

This listing is intended as an introduction to the literature on Artificial Intelligence, €”i.e., to the literature dealing with the problem of making machines behave intelligently. We have divided this area into categories and cross-indexed the references accordingly. Large bibliographies without some classification facility are next to useless. This particular field is still young, but there are already many instances in which workers have wasted much time in rediscovering (for better or for worse) schemes already reported. In the last year or two this problem has become worse, and in such a situation just about any information is better than none. This bibliography is intended to serve just that purpose-to present some information about this literature. The selection was confined mainly to publications directly concerned with construction of artificial problem-solving systems. Many peripheral areas are omitted completely or represented only by a few citations.IRE Trans. on Human Factors in Electronics, HFE-2, pages 39-55

... The literature does not include any general discussion of the outstanding problems of this field. In this article, an attempt will be made to separate out, analyze, and find the relations between some of these problems. Analysis will be supported with enough examples from the literature to serve the introductory function of a review article, but there remains much relevant work not described here.Proc. Institute of Radio Engineers 49, p. 8-30

Men typically communicate with computers in a variety of artificial,stylized, unambiguous languages that are better adapted to the machinethan to the man. For convenience and speed, many future computercenteredsystems will require men to communicate with computers innatural language. The business executive, the military commander, and thescientist need to ask questions of the computer in ordinary English, andto have the computer answer the questions directly. Baseball is a first steptoward this goal.Proc. Western Joint Computer Conference 19:555-570.

See also: Western Joint Computer Conference, May, 1962

The complete rules for coding in Information Processing Language-V (IPL-V), and the documentation of extensions incorporated since publication of the Information Processing Language-V Manual. A summary of extensions and the minor modifications to the language is contained in the final section. An index, a list of the basic IPL-V processes, and a full-scale copy of the coding sheet appear at the end of the Memorandum.See also: Google Books.Prentice·Hall, Englewood Cliffs, NJ.

Also available at RandJACM, 8 (3), 404-17

The investment process is a problem in decision-making under uncertainty. Our model, written as a computer program, simulates the proce- dures used in choosing investment policies for particular accounts, in evaluating the alternatives presented by the market, and in selecting the required portfolios. The analysis is based on the operations at a medium-sized national bank 1 and the decision-maker of our model is the trust imvestment officer. From A Simulation of Trust Investment, Englewood Cliffs, N.J.: Prentice-Hall, 1961.

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.

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).