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.

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.

The suggestion is based on the similarity of behaviour of these formal systems and or animals. The design of classification computers is discussed in the first paper; the design of conditional probability computers Is discussed in a third paper (Uttley, 1958, ref. 15); in both papers working models are described. FUrther reference to these papers will be by date only. It is the aim of the present paper to consider whether the two principles might operate in nervous systems. Mere are four requirements for the principle of classification to operate in an area of a nervous system.

THE application of learning machines to process control is discussed. Three approaches to the design of learning machines are shown to have more in common than is immediately apparent. These are (1) based on the use of conditional probabilities, (2) suggested by the idea that biological learning is due to facilitation of synapses and (3) based on existing statistical theory dealing with the optimisation of operating conditions. Although the application of logical-type machines to process control involves formidable complexity, design principles are evolved here for a learning machine which deals with quantitative signal and depends for its operation on the computation of correlation coefficients.

This third symbol indicates the pathological symptoms about which we have no information at all.

I do so here with a diffidence that will need no explanation to anyone whose ideas have been on the move for ten years. I am only thankful - and a little surprised - to find as much as I do with which I - and apparently others - now agree.

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.

Particular attention is given to processes involving pattern recognition, learning, planning ahead, and the use of analogies or?models!. Also considered is the question of designing "administrative" procedures to manage the use of these other devices. The paper begins with a discussion of what is meant by "Intelligence" and concludes with a sec-- tion concerned with some techniques through which a machine might further improve itself by adding to Its collection of problem--solving methods. I. INTELLIGENCE I feel that it would not be useful to lay down any absolute defini-- tion of "intelligence" or of "intelligent behaviour". For our goals in trying to design "thinking machines" are constantly changing in relation to our ever--increasing resources in this area. Certainly there are many kinds of performances which if exhibited by a man we would all agree, today, require or manifest intelligence. But would we agree tomorrow?

The paper examines the extent to which a less mechanistic approach may be possible and suggests limitations that may be imposed not only by human limitations but by difficulties of correspondence and significance between machine and manual situations. 1. INTRODUCTION LET us assume that automatic data processing (A.D.P.) can do the things that we are planning for it to do at present, such as payroll, stores accounting, and statistical analyses. 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.

Proceedings of the Symposium on the Mechanisation of Thought Processes.Teddington, Middlesex, England: National Physical Laboratory.