Technology
Pattern Recognition and Reading by Machine
"MANY EFFORTS have been made to discriminate, categorize, and quantitate patterns, and to reduce them into a usable machine language. The results have ordinarily been methods or devices with a high degree of specificity. For example, some devices require a special type font; others can read only one type font; still others require magnetic ink. We have an interest in decision-making circuits with the following qualities: (1) measurable high reliability in decision making, (2) either a high or a low reliability input, and (3) possibly low reliability components. The high specificity of the devices and methods mentioned above was felt to be a drawback for our purposes. All of these approaches prove upon inspection to center upon analysis of the specific characteristics of patterns into parts, followed by a synthesis of the whole from the parts. In these studies, pattern recognition of the whole, that is, Gestalt recognition, was chosen as a more fruitful avenue of approach and as a satisfactory problem for the initial phases of the over-all study." Proceedings of the Eastern Joint Computer Conference, pp. 225-232, New York: Association for Computing Machinery
Some methods of artificial intelligence and heuristic programming
In Proceedings of the Symposium on Mechanisation of Thought Processes, National Physical Laboratory, Teddington, England, London: H. M. Stationary Office, pp. 3-36
Some studies in machine learning using the game of checkers
The studies reported here have been concerned with the programming of a digital computer to behave in a way which, if done by human beings oranimals, would be described as involving the process of learning. Whilethis is not the place to dwell on the importance of machine-learning procedures,or to discourse on the philosophical aspects,1 there is obviously avery large amount of work, now done by people, which is quite trivial inits demands on the intellect but does, nevertheless, involve some learning.Also in Computers and Thought. Feigenbaum, Edward A. and Julian Feldman (Editors) 1963.See also:IEEE XploreSome Studies in Machine Learning Using the Game of Checkers, II - Recent ProgressIBM Journal of Research and Development, 3:211-229
Intelligent behavior in problem solving machines
IBM J. Research and Development 2:336-345
Elements of a theory of human problem solving
A description of a theory of problem-solving in terms of information processes amenable for use in a digital computer. The postulates are: "A control system consisting of a number of memories, which contain symbolized information and are interconnected by various ordering relations; a number of primitive information processes, which operate on the information in the memories; a perfectly definite set of rules for combining these processes into whole programs of processing." Examples are given of how processes that occur in behavior can be realized out of elementary information processes. The heuristic value of this theory is pertinent to theories of learning, perception, and concept formation. Psychological Review, March, 65(3):151-166.
Maximum likelihood estimation from incomplete data
Biometrics is a scientific journal emphasizing the role of statistics and mathematics in the biological sciences. Its object is to promote and extend the use of mathematical and statistical methods in pure and applied biological sciences by describing developments in these methods and their applications in a form readily assimilable by experimental scientists. JSTOR provides a digital archive of the print version of Biometrics. Authorized users may be able to access the full text articles at this site.