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 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
Two theorems of statistical seperability in the Perceptron
Frank Rosenblatt, born in New Rochelle, New York, U.S.A., July 11, 1928, graduated from Cornell University in 1950, and received a PhD degree in psychology, from the same university, in 1956. He was engaged in research on schizophrenia, as a Fellow of the U.S. Public Health Service, 1951-1953. He has made contributions to techniques of multivariate analysis, psychopathology, information processing and control systems, and physiological brain models. He is currently a Research Psychologist at the Cornell Aeronautical Laboratory, Inc., in Buffalo, New York, where he Is Project Engineer responsible for Project PARA (Perceiving and Recognizing Automaton). FRANK ROSENBLATT SUMMARY A THEORETICAL brain model, the perceptron, has been developed at the Cornell Aeronautical Laboratory, In Buffalo, New York. The perceptron is a probabilistic system, capable of learning to recognize and differentiate stimuli in its environment. Previous reports have covered the theory of a class of perceptrons ...
Pandemonium: A Paradigm for Learning
G. Selfridge was born in London 10 May PANDEMONIUM: A PARADIGM FOR LEARNING O. G. SELFRIDGE INTRODUCTION WE are proposing here a model of a process which we claim can adaptively improve itself to handle certain pattern recognition problems Which cannot be adequately specified in advance. Such problems are usual when trying' to build a machine to Imitate any one of a very large class of human data processing techniques. A speech typewriter is a good example of something that very many people have been trying unsuccessfully to build for some time. We do not suggest that we have proposed a model which can learn to typewrite from merely hearing speech. Pandemonium does not, however, seem on paper to have the same kinds of inherent restrictions or inflexibility that many previous proposals have had. The basic motif behind our model is the Inn of parallel processing. This is suggested on two grounds: first, it is often easier to handle data in a parallel manner, and, indeed, it is usually the more "natural" manner to handle it in; and, secondly, it is easier to modify an assembly of quasi We are not going to apologize for a frequent use of anthropomorphic or biamorphic terminology.
Tigris and Euphrates: A comparison between human and machine translation
Everything symbolized by a set of symbols constitutes the domain of symbolization of the set. The ultimate elements of the domain which symbolize nothing further are designated the terminal ind1catum. Most domains of symbolization comprise mediate symbols which are both symbolized by other symbols and themselves indicate further symbols. Mental concepts are treated as symbols. In translation, a set of symbols is transformed to another set in another language, the two sets having terminal indicata that only differ within narrow limits.
The Logic of Scientific Discovery
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Automation in the legal world
Dr. Lucien Mehl, born 1919 in Paris, studied at the University, Paris where he obtained his degrees in Philosophy and Law, and a Diploma of Advanced Studies in Political Economy and at the National School of Administration. He is now'Maitre des Requetesi to the Council of State and Director of external training at the National School of Administration. He is a member of the International Fiscal Association, the International Cybernetics Association and the French Operational Research Society. He has published a number of articles on administrative science, law, cybernetics and operational research. LUCIEN HEEL INTRODUCTION I. It may seem an ambitious step to try to apply mechanization or automation to the legal sciences. However, a machine for processing information can be an effective aid in searching for sources of legal information, in developing legal argument, in preparing the decision of the administrator or judge, and finally in checking the coherence of solutions arrived at. In the first place, much preliminary work is needed for introducing automation in legal affairs, and so much work can only be decided upon if it is found to be of definite use. Secondly, such an undertaking is not without its risks; the jurist may lose direct contact with the sources of law and no longer have the benefit of the intellectual activity involved in searching for information. Lastly, as a result of mechanization of this kind, thought may itself become inflexible, diminishing creative power and innovative effort. Nowadays, however, machine processing of information is becoming essential; "Homo sapiens" is in fact exposed to the risk of being overwhelmed by the vast accumulation of knowledge. It is becoming increasingly difficult to gain access to the sources of ideas, and the researcher wastes valuable time and often intensive mental effort in detailed and unprofitable research, never being sure whether his investigations will be fruitful, or whether he will not bypass the essential information. Moreover, it happens that writers doing research in the same field of knowledge are unaware of one another's work; and besides this, the difficulty of finding the information required makes the researchers specialize still more. They find it hard to link up the different disciplines, because they are generally doomed to remain in ignorance of everything outside their on customary field of investigation. In legal matters, the number of laws and regulations and the scope of jurisprudence are growing on an alarming scale, and everyone is complaining about the situation - administrators and judges, as well as those dealt with under the law.