In this paper we present a new algorithm for searching trees. The algorithm, which we have named For this reason, the search is usually limited in some way (e.g., number of nodes B*, finds a proof that an arc at the root of a search tree is better than any other. It does this by to be expanded, or maximum depth to which it may go).

Human programmers seem to know a lot about programming. This suggests a way to try to build here was designed to shed some light on questions like these.

R. L. GREGORY, Psychological Laboratory, Cambridge Discussion on paper 5 683 6 Some questions concerning the explanation of learning 691 in animals MR. A. J. WATS01,4 Psychological Laboratory, Cambridge Discussion on paper 6 721 7 Information, redundancy and decay of the memory trace 729 DR. Y. BAR-HILLEL, The Hebrew University, Jerusalem Discussion on paper 2 801 3 To what extent can administration be mechanized?

There will, of course, be many problems to be solved before these tasks can be regarded as satisfactorily completed, and before we can speak with confidence out of experience. But these problems do not appear to have any fundamentally insuperable content. The difficul-- ties are manmade rather than intrinsic. They originate in part from the difficulty of adjusting the organisms of office life to new rhythms, new environments, new relationships, in part from imperfect understanding and appreciation of the power and range of new techniques, and in part from a lack of perception of the limitations and deficiencies of these systems. We may reasonably suppose that, during the course of the next five years, these difficulties will be overcome and that, throughout Government Departments and Industry, there will be a growing number of installations at work on these jobs. With this perhaps over--simplified premise, it is not too early to start thinking about a possible future form of A.D.P. in Government Departments in, say, ten or fifteen years' time.

I am quite ready to subscribe to the already mentioned slogan that "whatever a human being can do,an appropriate machine can do, too"; but I do this only because.I regard the slogan as utterly trivial. At the moment, I am not talking about what maohines could do in principle but only about what actually existing or blueprinted machines could do, and it Is with regard to these that I utter my definite opinions. If someone wishes to write sciencefiction about information-processing centres of the (undetermined) future, let him do so and I shall discuss it with him over a glass of beer and even offer some startling suggestions of my own. If he is interested in improving the literature search process today, I would strongly advise him to forget about mechanizing abstracting or indexing. May I add that it is with a good amount of sorrow that I have come to this conclusion which is quite counter, to my temperament and my convictions (never published) of a few years ago.

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. 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.

Dr. Francois Paycha, born at Narbonne, studied medicine at the University of Montpellier. His first researches were concerned with the embryology of the eye, later using the distribution of radioactive phosphorus P32 to study the structure of the tissues and for the detection of tumours. He was then appointed to the National Centre of Scientific Research. While in charge of a hospital clinic, he noted the considerable differences in the diagnoses of conscientious and knowledgeable practitioners and those advanced by the hospital. In view of the special need for exact diagnosis in medicine he made a study of the causes of these differences. After theoretical research, he made the first "Medical Memory' in 1953 with the help of Bull and later of I.B.M. He studied the structure of a three-symbol logic which is applicable to medical' problems and in general. After a year in the service of Prof. G. E. Jayle, he abandoned pure research and entered industry. SUMMARY I am going to analyse ...

Oliver G. Selfridge was born in London 10 May 1926. He studied at the Massachusetts Institute of Technology from 1942-1945, returning postgraduately from 1946-1950. After 2 years at Signal Corps Laboratories at Fort Monmouth, New Jersey, he joined Lincoln Laboratories in Group 34, Communication Techniques, of which he is now Group Leader. 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.

The extent to which parallels between brains and machines may profitably be drawn has been discussed by many writers including MacKay (ref. 1) and Sluckin (ref.

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). 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 based on ...