to program the machine

1) Автоматика: программировать (обработку) на станке

2) Макаров: программировать обработку на станке

- overhead way machine

- 2D machining program

1) (Amer.) see academic.ru/58260/programme">programme 1.

2) (Computing, Electronics) Programm, das

1) (Amer.) see programme 2.

2) (Computing, Electronics) programmieren

* * *

verb - present participle programming ( American also programing): past tense, past participle programmed ( American also programed) - (to give information, instructions etc to (a machine, especially a computer, so that it can do a particular job).) programmieren

* * *

[ˈprəʊgræm, AM ˈproʊ-]

I. n

1. COMPUT Programm nt

to write a \program ein Programm schreiben

2. esp AM, AUS see programme

▶ to get with the \program ( fam) sich akk sammeln

II. vt

1. COMPUT

▪ to \program sth etw programmieren

2. esp AM, AUS see programme

AM pro·gram

[AM ˈproʊ-]

I. n

1. RADIO, TV Programm nt, Sendefolge f; (single broadcast) Sendung f

2. (list of events) Programm nt; THEAT (for all plays) Spielplan m; (for one play) Programmheft nt

3. (plan) Programm nt, Plan m

what's on the \program for today? was steht heute auf dem Programm?

fitness/modernization \program Fitness-/Modernisierungsprogramm nt

II. vt

1. (instruct)

▪ to \program sth etw programmieren

to \program a VCR einen Videorecorder programmieren [o einstellen

2. usu passive (mentally train)

▪ to \program sb to do sth jdn darauf programmieren, etw zu tun

I'm \programd to wake up at seven ich wache automatisch um sieben Uhr auf

▪ to \program oneself to do sth sich dat etw angewöhnen

* * *

1. n

2. vt

* * *

program¹, besonders Br programme [ˈprəʊɡræm]

A s

1. (Studien-, Partei- etc) Programm n:

what’s the program for today? umg was steht heute auf dem Programm?

2. THEAT etc Programm n:

a) Spielplan m

b) Programmheft n

c) Darbietung f:

program music Programmmusik f;

program picture Beifilm m;

program seller Programmverkäufer(in)

3. RADIO, TV Programm n:

a) Sendefolge f

b) Sendung f:

to be on the program im Programm sein, auf dem Programm stehen;

program director Programmdirektor(in);

program policy Programmpolitik f;

program slot Programmplatz m

4. Lehrplan m

B v/t prät und pperf -grammed, US auch -gramed

1. ein Programm aufstellen oder zusammenstellen für

2. auf das Programm setzen, ansetzen

3. planen, vorbereiten

program², Br auch programme [ˈprəʊɡræm] IT

A s Programm n:

program-controlled programmgesteuert;

program exit Ausgang m;

program library Programmbibliothek f;

program sequence Programmfolge f;

program step Programmschritt m

B v/t prät und pperf -grammed, US auch -gramed programmieren (auch fig):

to program sth to do sth etwas so programmieren, dass es etwas tut;

programmed instruction SCHULE programmierter Unterricht

prog. abk

1. program (programme) Progr.

2. progress

3. progressive

* * *

1) (Amer.) see programme 1.

2) (Computing, Electronics) Programm, das

1) (Amer.) see programme 2.

2) (Computing, Electronics) programmieren

* * *

Sendung -en f. (US) n.

Programm -e n. v.

programmieren v.

verb - present participle programming (American also programing): past tense, past participle programmed (American also programed) - (to give information, instructions etc to (a machine, especially a computer, so that it can do a particular job).) programar

program¹ n programa

program² vb programar

tr['prəʊgræm]

noun

1 SMALLCOMPUTING/SMALL programa nombre masculino

2 SMALLAMERICAN ENGLISH/SMALL→ link=programme programme{

transitive verb (pt & pp programmed, ger programming)

1 SMALLCOMPUTING/SMALL programar

2 SMALLAMERICAN ENGLISH/SMALL→ link=programme programme{

program ['pro:.græm, -grəm] vt, - grammed or - gramed ; - gramming or - graming : programar

program n

: programa m

program (US)

• cartel s.m.

• programa s.m. (Theater) (US)

• programa (Teatro) (ESP) s.m. (US) (Computing)

• programar (Informática) v. (US)

• programar v.

1)

a) ( schedule) programa m

b) (for a performance, concert) programa m

c) (esp AmE Educ) ( course) curso m; ( syllabus) programa m

2) ( plan) programa m

3) (Rad, TV) programa m

4) ( on household appliance) programa m

5) program ( Comput) programa m

1) BrE also programme

a) ( schedule) \<\<activities\>\> programar, planear

b) ( instruct) programar

2) ( Comput) programar

vi ( Comput) programar

N programa m

VT programar

VI programar

* * *

1)

a) ( schedule) programa m

b) (for a performance, concert) programa m

c) (esp AmE Educ) ( course) curso m; ( syllabus) programa m

2) ( plan) programa m

3) (Rad, TV) programa m

4) ( on household appliance) programa m

5) program ( Comput) programa m

1) BrE also programme

a) ( schedule) \<\<activities\>\> programar, planear

b) ( instruct) programar

2) ( Comput) programar

vi ( Comput) programar

verb - present participle programming (American also programing): past tense, past participle programmed (American also programed) - (to give information, instructions etc to (a machine, especially a computer, so that it can do a particular job).) programar

* * *

[pr'ougræm] n Amer 1 programa: a) impresso informativo sobre um espetáculo. b) execução ou desenrolar de um espetáculo. c) projeto, plano. 2 prolegômenos, prefácio. 3 Comp programa. • vt programar. program of government programa de governo. school lunch program merenda escolar. to draw up a program estabelecer um plano de trabalho. what is the program for today? que faremos hoje?

    The Formal Structure of the Virtual Machine

   wo programs can be thought of as strongly equivalent or as different realizations of the same algorithm or the same cognitive process if they can be represented by the same program in some theoretically specified virtual machine. A simple way of stating this is to say that we individuate cognitive processes in terms of their expression in the canonical language of this virtual machine. The formal structure of the virtual machine-or what I call its functional architecture-thus represents the theoretical definition of, for example, the right level of specificity (or level of aggregation) at which to view mental processes, the sort of functional resources the brain makes available-what operations are primitive, how memory is organized and accessed, what sequences are allowed, what limitations exist on the passing of arguments and on the capacities of various buffers, and so on. (Pylyshyn, 1984, p. 92)

Automation: program the machine

   1) The Parallel Nature of Feedback in Living Individuals and Communication Machines

   It is my thesis that the physical functioning of the living individual and the operation of some of the newer communication machines are precisely parallel in their analogous attempts to control entropy through feedback. Both of them have sensory receptors as one stage of their cycle of operation: that is, in both of them there exists a special apparatus for collecting information from the outer world at low energy levels, and for making it available in the operation of the individual or of the machine.

   In both cases these external messages are not taken neat, but through the internal transforming powers of the apparatus, whether it be alive or dead. The information is then turned into a new form available for the further stages of performance. In both the animal and the machine this performance is made to be effective on the outer world. In both of them, their performed action on the outer world, and not merely their intended action, is reported back to the central regulatory apparatus. (Wiener, 1954, pp. 26-27)

   2) The Study of Information Transfer

   [The job of the cyberneticist] is the study of information transfer: the converting of information from one form to another-the human voice into radio waves and back into sound once more, or a complex mathematical equation into a set of punched holes on a tape, to be fed into a computer and then into a set of traces on reels of magnetic tape in the computer's "memory store."... To him, protein synthesis is just such another case. The mechanism for ensuring the exact replication of a protein chain by a new cell is that of transferring the information about the protein structure from the parent to the daughter cell. (Rose, 1970, p. 162)

   3) Why Computational Devices Are Likely to Be Literal Minded

   The theme of all these tales [("Fisherman and the Jinni" in the Thousand Nights and a Night; The Sorcerer's Apprentice; and "The Monkey's Paw" by W. W. Jacobs)] is the danger of magic. This seems to lie in the fact that the operation of magic is singularly literal-minded, and that if it grants you anything at all it grants what you ask for, not what you should have asked for or what you intend....

   The magic of automation, and in particular the magic of an automatization in which the devices learn, may be expected to be similarly literal-minded. If you are playing a game according to certain rules and set the playing-machine to play for victory, you will get victory if you get anything at all, and the machine will not pay the slightest attention to any consideration except victory according to the rules. If you are playing a war game with a certain conventional interpretation of victory, victory will be the goal at any cost, even that of the extermination of your own side, unless this condition of survival is explicitly contained in the definition of victory according to which you program the machine. (Wiener, 1964, pp. 59-60)

1) Engineering: program a machine (обработку)

2) Automation: (обработку) program the machine

   1) Programs and the Complexity of Human Mental Processes

   In my opinion, none of [these programs] does even remote justice to the complexity of human mental processes. Unlike men, "artificially intelligent" programs tend to be single minded, undistractable, and unemotional. (Neisser, 1967, p. 9)

   2) Artificial Intelligence Is an Engineering Discipline

   Future progress in [artificial intelligence] will depend on the development of both practical and theoretical knowledge.... As regards theoretical knowledge, some have sought a unified theory of artificial intelligence. My view is that artificial intelligence is (or soon will be) an engineering discipline since its primary goal is to build things. (Nilsson, 1971, pp. vii-viii)

   3) A Sceptical View of Artificial Intelligence

   Most workers in AI [artificial intelligence] research and in related fields confess to a pronounced feeling of disappointment in what has been achieved in the last 25 years. Workers entered the field around 1950, and even around 1960, with high hopes that are very far from being realized in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.... In the meantime, claims and predictions regarding the potential results of AI research had been publicized which went even farther than the expectations of the majority of workers in the field, whose embarrassments have been added to by the lamentable failure of such inflated predictions....

   When able and respected scientists write in letters to the present author that AI, the major goal of computing science, represents "another step in the general process of evolution"; that possibilities in the 1980s include an all-purpose intelligence on a human-scale knowledge base; that awe-inspiring possibilities suggest themselves based on machine intelligence exceeding human intelligence by the year 2000 [one has the right to be skeptical]. (Lighthill, 1972, p. 17)

   4) Just as Astronomy Succeeded Astrology, the Discovery of Intellectual Processes in Machines Should Lead to a Science, Eventually

   Just as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)

   5) Problems in Machine Intelligence Arise Because Things Obvious to Any Person Are Not Represented in the Program

   Many problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)

   6) The Meaning of a Symbolic Description

   What do we mean by [a symbolic] "description"? We do not mean to suggest that our descriptions must be made of strings of ordinary language words (although they might be). The simplest kind of description is a structure in which some features of a situation are represented by single ("primitive") symbols, and relations between those features are represented by other symbols-or by other features of the way the description is put together. (Minsky & Papert, 1973, p. 11)

   7) The Principle of Artificial Intelligence

   [AI is] the use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular. (Boden, 1977, p. 5)

   8) Artificial Intelligence Recognizes the Need for Knowledge in Its Systems

   The word you look for and hardly ever see in the early AI literature is the word knowledge. They didn't believe you have to know anything, you could always rework it all.... In fact 1967 is the turning point in my mind when there was enough feeling that the old ideas of general principles had to go.... I came up with an argument for what I called the primacy of expertise, and at the time I called the other guys the generalists. (Moses, quoted in McCorduck, 1979, pp. 228-229)

   9) Artificial Intelligence Is Psychology in a Particularly Pure and Abstract Form

   The basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)

    10) There Are Many Types of Reasoning

   There are many different kinds of reasoning one might imagine:

    Formal reasoning involves the syntactic manipulation of data structures to deduce new ones following prespecified rules of inference. Mathematical logic is the archetypical formal representation. Procedural reasoning uses simulation to answer questions and solve problems. When we use a program to answer What is the sum of 3 and 4? it uses, or "runs," a procedural model of arithmetic. Reasoning by analogy seems to be a very natural mode of thought for humans but, so far, difficult to accomplish in AI programs. The idea is that when you ask the question Can robins fly? the system might reason that "robins are like sparrows, and I know that sparrows can fly, so robins probably can fly."

    Generalization and abstraction are also natural reasoning process for humans that are difficult to pin down well enough to implement in a program. If one knows that Robins have wings, that Sparrows have wings, and that Blue jays have wings, eventually one will believe that All birds have wings. This capability may be at the core of most human learning, but it has not yet become a useful technique in AI.... Meta- level reasoning is demonstrated by the way one answers the question What is Paul Newman's telephone number? You might reason that "if I knew Paul Newman's number, I would know that I knew it, because it is a notable fact." This involves using "knowledge about what you know," in particular, about the extent of your knowledge and about the importance of certain facts. Recent research in psychology and AI indicates that meta-level reasoning may play a central role in human cognitive processing. (Barr & Feigenbaum, 1981, pp. 146-147)

    11) Programs Are Beginning to Do Things That Critics Have Asserted to Be Impossible

   Suffice it to say that programs already exist that can do things-or, at the very least, appear to be beginning to do things-which ill-informed critics have asserted a priori to be impossible. Examples include: perceiving in a holistic as opposed to an atomistic way; using language creatively; translating sensibly from one language to another by way of a language-neutral semantic representation; planning acts in a broad and sketchy fashion, the details being decided only in execution; distinguishing between different species of emotional reaction according to the psychological context of the subject. (Boden, 1981, p. 33)

    12) The Synthesis of Man and Machine

   Can the synthesis of Man and Machine ever be stable, or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens-and I have... good reasons for thinking that it must-we have nothing to regret and certainly nothing to fear. (Clarke, 1984, p. 243)

    13) The Thesis of Good Old-Fashioned Artificial Intelligence (GOFAI)

   The thesis of GOFAI... is not that the processes underlying intelligence can be described symbolically... but that they are symbolic. (Haugeland, 1985, p. 113)

    14) Artificial Intelligence Provides a Useful Approach to Psychological and Psychiatric Theory Formation

   It is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)

    15) Four Kinds of Artificial Intelligence

   We might distinguish among four kinds of AI.

   ♦ Nonpsychological AI

   Research of this kind involves building and programming computers to perform tasks which, to paraphrase Marvin Minsky, would require intelligence if they were done by us. Researchers in nonpsychological AI make no claims whatsoever about the psychological realism of their programs or the devices they build, that is, about whether or not computers perform tasks as humans do.

   ♦ Weak Psychological AI

   Research here is guided by the view that the computer is a useful tool in the study of mind. In particular, we can write computer programs or build devices that simulate alleged psychological processes in humans and then test our predictions about how the alleged processes work. We can weave these programs and devices together with other programs and devices that simulate different alleged mental processes and thereby test the degree to which the AI system as a whole simulates human mentality. According to weak psychological AI, working with computer models is a way of refining and testing hypotheses about processes that are allegedly realized in human minds.

   ♦ Strong Psychological AI

... According to this view, our minds are computers and therefore can be duplicated by other computers. Sherry Turkle writes that the "real ambition is of mythic proportions, making a general purpose intelligence, a mind." (Turkle, 1984, p. 240) The authors of a major text announce that "the ultimate goal of AI research is to build a person or, more humbly, an animal." (Charniak & McDermott, 1985, p. 7)

   ♦ Suprapsychological AI

   Research in this field, like strong psychological AI, takes seriously the functionalist view that mentality can be realized in many different types of physical devices. Suprapsychological AI, however, accuses strong psychological AI of being chauvinisticof being only interested in human intelligence! Suprapsychological AI claims to be interested in all the conceivable ways intelligence can be realized. (Flanagan, 1991, pp. 241-242)

    16) Determination of Relevance of Rules in Particular Contexts

   Even if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)

    17) Form and Content Are Not Fundamentally Different

   Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)

    18) The Assumption That the Mind Is a Formal System

   Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)

    19) A Statement of the Primary and Secondary Purposes of Artificial Intelligence

   The primary goal of Artificial Intelligence is to make machines smarter.

   The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)

    20) Mathematical Logic Provides the Basis for Theory in AI

   The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....

   AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)

    21) Perceptual Structures Can Be Represented as Lists of Elementary Propositions

   In artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)

    22) Definitions of Artificial Intelligence

   Artificial intelligence (AI) is sometimes defined as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do. Some of these things are commonly regarded as requiring intelligence: offering a medical diagnosis and/or prescription, giving legal or scientific advice, proving theorems in logic or mathematics. Others are not, because they can be done by all normal adults irrespective of educational background (and sometimes by non-human animals too), and typically involve no conscious control: seeing things in sunlight and shadows, finding a path through cluttered terrain, fitting pegs into holes, speaking one's own native tongue, and using one's common sense. Because it covers AI research dealing with both these classes of mental capacity, this definition is preferable to one describing AI as making computers do "things that would require intelligence if done by people." However, it presupposes that computers could do what minds can do, that they might really diagnose, advise, infer, and understand. One could avoid this problematic assumption (and also side-step questions about whether computers do things in the same way as we do) by defining AI instead as "the development of computers whose observable performance has features which in humans we would attribute to mental processes." This bland characterization would be acceptable to some AI workers, especially amongst those focusing on the production of technological tools for commercial purposes. But many others would favour a more controversial definition, seeing AI as the science of intelligence in general-or, more accurately, as the intellectual core of cognitive science. As such, its goal is to provide a systematic theory that can explain (and perhaps enable us to replicate) both the general categories of intentionality and the diverse psychological capacities grounded in them. (Boden, 1990b, pp. 1-2)

    23) The Computer Can Not Be a Model of the Mind

   Because the ability to store data somewhat corresponds to what we call memory in human beings, and because the ability to follow logical procedures somewhat corresponds to what we call reasoning in human beings, many members of the cult have concluded that what computers do somewhat corresponds to what we call thinking. It is no great difficulty to persuade the general public of that conclusion since computers process data very fast in small spaces well below the level of visibility; they do not look like other machines when they are at work. They seem to be running along as smoothly and silently as the brain does when it remembers and reasons and thinks. On the other hand, those who design and build computers know exactly how the machines are working down in the hidden depths of their semiconductors. Computers can be taken apart, scrutinized, and put back together. Their activities can be tracked, analyzed, measured, and thus clearly understood-which is far from possible with the brain. This gives rise to the tempting assumption on the part of the builders and designers that computers can tell us something about brains, indeed, that the computer can serve as a model of the mind, which then comes to be seen as some manner of information processing machine, and possibly not as good at the job as the machine. (Roszak, 1994, pp. xiv-xv)

    24) Computers Will Not Always Be Inferior to Human Brains

   The inner workings of the human mind are far more intricate than the most complicated systems of modern technology. Researchers in the field of artificial intelligence have been attempting to develop programs that will enable computers to display intelligent behavior. Although this field has been an active one for more than thirty-five years and has had many notable successes, AI researchers still do not know how to create a program that matches human intelligence. No existing program can recall facts, solve problems, reason, learn, and process language with human facility. This lack of success has occurred not because computers are inferior to human brains but rather because we do not yet know in sufficient detail how intelligence is organized in the brain. (Anderson, 1995, p. 2)

programme [pʀɔgʀam]

   a. [de cinéma, concert, radio, télévision] programme (Brit), program (US)

• au programme on the programme

   b. ( = brochure) [de cinéma, théâtre, concert] programme (Brit), program (US) ; [de radio, télévision] guide ; ( = section de journal) listings

   c. (School) [de matière] syllabus ; [de classe, école] curriculum

• le programme de français the French syllabus

• quel est le programme cette année ? what's on the curriculum this year?

• les œuvres au programme the set (Brit) or assigned (US) books

   d. ( = projet) programme (Brit), program (US)

• programme d'action programme of action

• programme de travail work plan

• programme électoral election platform

• c'est tout un programme ! (inf) that'll take some doing!

   e. ( = calendrier) programme (Brit), program (US)

• j'ai un programme très chargé I have a very busy timetable

• ce n'était pas prévu au programme that wasn't on the agenda

   f. [de machine à laver] programme (Brit), program (US) ; (Computing) program

   g. (Sport) programme (Brit), program (US)

• programme libre [de patinage artistique] free skating

* * *

nom masculin

1) Cinéma, Radio, Théâtre, Télévision programme [BrE]

2) ( emploi du temps) programme [BrE]

3) ( projet) ( d'action) plan; ( de travail) programme [BrE]

4) École, Université syllabus

5) Informatique program

* * *

1) (projet, grille) programme Grande-Bretagne program USA

2) TV, RADIO programme Grande-Bretagne program USA

3) ÉDUCATION syllabus, curriculum

4) INFORMATIQUE program

* * *

programme nm

1 Radio, Théât, TV, Cin programme^GB; ce n'est pas au programme lit it's not on the programme^GB; fig that wasn't planned; changement de programme lit change in the ou of programme^GB; fig change of plan;

2 ( emploi du temps) programme^GB; le programme de la journée the programme^GB for the day; avoir un programme très chargé to have a very busy schedule; quel est le programme des réjouissances aujourd'hui? hum what delights are in store (for us) today?;

3 ( projet) ( d'action) plan; ( de travail) programme^GB; programme électoral electoral programme^GB ou platform; programme de gouvernement government programme^GB ou platform; c'est tout un programme! hum that'll take some doing!;

4 Scol, Univ syllabus; le programme d'histoire the History syllabus; le programme de première année the first-year syllabus; au programme on the syllabus;

5 Ordinat program; programme d'exploitation/de compilation operating/compiling program; programme machine/d'assemblage computer/assembly program.

[prɔgram] nom masculin

1. [contenu - d'une cérémonie, d'un spectacle] programme

2. [brochure - d'un concert, d'une soirée] programme ; [ - de cinéma, de télévision] listings, guide

3. [emploi du temps] schedule

4. ÉDUCATION [d'une année] curriculum

[dans une matière] syllabus

5. POLITIQUE [plate-forme] manifesto (UK), platform (US)

6. [projet] programme

7. INFORMATIQUE program

programme [pʀɔgʀam]

   a. [de cinéma, concert, radio, télévision] programme (Brit), program (US)

• au programme on the programme

   b. ( = brochure) [de cinéma, théâtre, concert] programme (Brit), program (US) ; [de radio, télévision] guide ; ( = section de journal) listings

   c. (School) [de matière] syllabus ; [de classe, école] curriculum

• le programme de français the French syllabus

• quel est le programme cette année ? what's on the curriculum this year?

• les œuvres au programme the set (Brit) or assigned (US) books

   d. ( = projet) programme (Brit), program (US)

• programme d'action programme of action

• programme de travail work plan

• programme électoral election platform

• c'est tout un programme ! (inf) that'll take some doing!

   e. ( = calendrier) programme (Brit), program (US)

• j'ai un programme très chargé I have a very busy timetable

• ce n'était pas prévu au programme that wasn't on the agenda

   f. [de machine à laver] programme (Brit), program (US) ; (Computing) program

   g. (Sport) programme (Brit), program (US)

• programme libre [de patinage artistique] free skating

* * *

nom masculin

1) Cinéma, Radio, Théâtre, Télévision programme [BrE]

2) ( emploi du temps) programme [BrE]

3) ( projet) ( d'action) plan; ( de travail) programme [BrE]

4) École, Université syllabus

5) Informatique program

* * *

1) (projet, grille) programme Grande-Bretagne program USA

2) TV, RADIO programme Grande-Bretagne program USA

3) ÉDUCATION syllabus, curriculum

4) INFORMATIQUE program