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1 underlying language
Большой англо-русский и русско-английский словарь > underlying language
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2 underlying language
1) <comput.> язык базовый
2) язык исходный -
3 underlying language
Математика: язык, лежащий в основе (напр., теории) -
4 underlying language
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5 language
- absolutely homogeneous language - absolutely inadequate language - absolutely nonhomogeneous language - absolutely nonperfect language - absolutely nonsimple language - absolutely perfect language - absolutely simple language - completely formalized language - completely homogeneous language - left categorial language - locally perfectly adequate language - locally simple language - locally strongly language - locally well adequate language - noncompletely homogeneous language - right categorial language - scattered context languageindistinguishable in the language — лог. неразличимый на языке, эквивалентный
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6 language
язык
– algebraic language
– algorithmic language
– assembler language
– code language
– computer-oriented language
– data-base language
– extensible language
– formalize language
– in everyday language
– information language
– input language
– job control language
– machine language
– mathematical language
– number language
– object language
– plex language
– program language
– programming language
– reference language
– typed language
– underlying language
autocovariance assembly language — <math.> автоковариация
information retrieval language — информационно-поисковый язык
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7 underlying
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8 Language
Philosophy is written in that great book, the universe, which is always open, right before our eyes. But one cannot understand this book without first learning to understand the language and to know the characters in which it is written. It is written in the language of mathematics, and the characters are triangles, circles, and other figures. Without these, one cannot understand a single word of it, and just wanders in a dark labyrinth. (Galileo, 1990, p. 232)It never happens that it [a nonhuman animal] arranges its speech in various ways in order to reply appropriately to everything that may be said in its presence, as even the lowest type of man can do. (Descartes, 1970a, p. 116)It is a very remarkable fact that there are none so depraved and stupid, without even excepting idiots, that they cannot arrange different words together, forming of them a statement by which they make known their thoughts; while, on the other hand, there is no other animal, however perfect and fortunately circumstanced it may be, which can do the same. (Descartes, 1967, p. 116)Human beings do not live in the object world alone, nor alone in the world of social activity as ordinarily understood, but are very much at the mercy of the particular language which has become the medium of expression for their society. It is quite an illusion to imagine that one adjusts to reality essentially without the use of language and that language is merely an incidental means of solving specific problems of communication or reflection. The fact of the matter is that the "real world" is to a large extent unconsciously built on the language habits of the group.... We see and hear and otherwise experience very largely as we do because the language habits of our community predispose certain choices of interpretation. (Sapir, 1921, p. 75)It powerfully conditions all our thinking about social problems and processes.... No two languages are ever sufficiently similar to be considered as representing the same social reality. The worlds in which different societies live are distinct worlds, not merely the same worlds with different labels attached. (Sapir, 1985, p. 162)[A list of language games, not meant to be exhaustive:]Giving orders, and obeying them- Describing the appearance of an object, or giving its measurements- Constructing an object from a description (a drawing)Reporting an eventSpeculating about an eventForming and testing a hypothesisPresenting the results of an experiment in tables and diagramsMaking up a story; and reading itPlay actingSinging catchesGuessing riddlesMaking a joke; and telling itSolving a problem in practical arithmeticTranslating from one language into anotherLANGUAGE Asking, thanking, cursing, greeting, and praying-. (Wittgenstein, 1953, Pt. I, No. 23, pp. 11 e-12 e)We dissect nature along lines laid down by our native languages.... The world is presented in a kaleidoscopic flux of impressions which has to be organized by our minds-and this means largely by the linguistic systems in our minds.... No individual is free to describe nature with absolute impartiality but is constrained to certain modes of interpretation even while he thinks himself most free. (Whorf, 1956, pp. 153, 213-214)We dissect nature along the lines laid down by our native languages.The categories and types that we isolate from the world of phenomena we do not find there because they stare every observer in the face; on the contrary, the world is presented in a kaleidoscopic flux of impressions which has to be organized by our minds-and this means largely by the linguistic systems in our minds.... We are thus introduced to a new principle of relativity, which holds that all observers are not led by the same physical evidence to the same picture of the universe, unless their linguistic backgrounds are similar or can in some way be calibrated. (Whorf, 1956, pp. 213-214)9) The Forms of a Person's Thoughts Are Controlled by Unperceived Patterns of His Own LanguageThe forms of a person's thoughts are controlled by inexorable laws of pattern of which he is unconscious. These patterns are the unperceived intricate systematizations of his own language-shown readily enough by a candid comparison and contrast with other languages, especially those of a different linguistic family. (Whorf, 1956, p. 252)It has come to be commonly held that many utterances which look like statements are either not intended at all, or only intended in part, to record or impart straightforward information about the facts.... Many traditional philosophical perplexities have arisen through a mistake-the mistake of taking as straightforward statements of fact utterances which are either (in interesting non-grammatical ways) nonsensical or else intended as something quite different. (Austin, 1962, pp. 2-3)In general, one might define a complex of semantic components connected by logical constants as a concept. The dictionary of a language is then a system of concepts in which a phonological form and certain syntactic and morphological characteristics are assigned to each concept. This system of concepts is structured by several types of relations. It is supplemented, furthermore, by redundancy or implicational rules..., representing general properties of the whole system of concepts.... At least a relevant part of these general rules is not bound to particular languages, but represents presumably universal structures of natural languages. They are not learned, but are rather a part of the human ability to acquire an arbitrary natural language. (Bierwisch, 1970, pp. 171-172)In studying the evolution of mind, we cannot guess to what extent there are physically possible alternatives to, say, transformational generative grammar, for an organism meeting certain other physical conditions characteristic of humans. Conceivably, there are none-or very few-in which case talk about evolution of the language capacity is beside the point. (Chomsky, 1972, p. 98)[It is] truth value rather than syntactic well-formedness that chiefly governs explicit verbal reinforcement by parents-which renders mildly paradoxical the fact that the usual product of such a training schedule is an adult whose speech is highly grammatical but not notably truthful. (R. O. Brown, 1973, p. 330)he conceptual base is responsible for formally representing the concepts underlying an utterance.... A given word in a language may or may not have one or more concepts underlying it.... On the sentential level, the utterances of a given language are encoded within a syntactic structure of that language. The basic construction of the sentential level is the sentence.The next highest level... is the conceptual level. We call the basic construction of this level the conceptualization. A conceptualization consists of concepts and certain relations among those concepts. We can consider that both levels exist at the same point in time and that for any unit on one level, some corresponding realizate exists on the other level. This realizate may be null or extremely complex.... Conceptualizations may relate to other conceptualizations by nesting or other specified relationships. (Schank, 1973, pp. 191-192)The mathematics of multi-dimensional interactive spaces and lattices, the projection of "computer behavior" on to possible models of cerebral functions, the theoretical and mechanical investigation of artificial intelligence, are producing a stream of sophisticated, often suggestive ideas.But it is, I believe, fair to say that nothing put forward until now in either theoretic design or mechanical mimicry comes even remotely in reach of the most rudimentary linguistic realities. (Steiner, 1975, p. 284)The step from the simple tool to the master tool, a tool to make tools (what we would now call a machine tool), seems to me indeed to parallel the final step to human language, which I call reconstitution. It expresses in a practical and social context the same understanding of hierarchy, and shows the same analysis by function as a basis for synthesis. (Bronowski, 1977, pp. 127-128)t is the language donn eґ in which we conduct our lives.... We have no other. And the danger is that formal linguistic models, in their loosely argued analogy with the axiomatic structure of the mathematical sciences, may block perception.... It is quite conceivable that, in language, continuous induction from simple, elemental units to more complex, realistic forms is not justified. The extent and formal "undecidability" of context-and every linguistic particle above the level of the phoneme is context-bound-may make it impossible, except in the most abstract, meta-linguistic sense, to pass from "pro-verbs," "kernals," or "deep deep structures" to actual speech. (Steiner, 1975, pp. 111-113)A higher-level formal language is an abstract machine. (Weizenbaum, 1976, p. 113)Jakobson sees metaphor and metonymy as the characteristic modes of binarily opposed polarities which between them underpin the two-fold process of selection and combination by which linguistic signs are formed.... Thus messages are constructed, as Saussure said, by a combination of a "horizontal" movement, which combines words together, and a "vertical" movement, which selects the particular words from the available inventory or "inner storehouse" of the language. The combinative (or syntagmatic) process manifests itself in contiguity (one word being placed next to another) and its mode is metonymic. The selective (or associative) process manifests itself in similarity (one word or concept being "like" another) and its mode is metaphoric. The "opposition" of metaphor and metonymy therefore may be said to represent in effect the essence of the total opposition between the synchronic mode of language (its immediate, coexistent, "vertical" relationships) and its diachronic mode (its sequential, successive, lineal progressive relationships). (Hawkes, 1977, pp. 77-78)It is striking that the layered structure that man has given to language constantly reappears in his analyses of nature. (Bronowski, 1977, p. 121)First, [an ideal intertheoretic reduction] provides us with a set of rules"correspondence rules" or "bridge laws," as the standard vernacular has it-which effect a mapping of the terms of the old theory (T o) onto a subset of the expressions of the new or reducing theory (T n). These rules guide the application of those selected expressions of T n in the following way: we are free to make singular applications of their correspondencerule doppelgangers in T o....Second, and equally important, a successful reduction ideally has the outcome that, under the term mapping effected by the correspondence rules, the central principles of T o (those of semantic and systematic importance) are mapped onto general sentences of T n that are theorems of Tn. (P. Churchland, 1979, p. 81)If non-linguistic factors must be included in grammar: beliefs, attitudes, etc. [this would] amount to a rejection of the initial idealization of language as an object of study. A priori such a move cannot be ruled out, but it must be empirically motivated. If it proves to be correct, I would conclude that language is a chaos that is not worth studying.... Note that the question is not whether beliefs or attitudes, and so on, play a role in linguistic behavior and linguistic judgments... [but rather] whether distinct cognitive structures can be identified, which interact in the real use of language and linguistic judgments, the grammatical system being one of these. (Chomsky, 1979, pp. 140, 152-153)23) Language Is Inevitably Influenced by Specific Contexts of Human InteractionLanguage cannot be studied in isolation from the investigation of "rationality." It cannot afford to neglect our everyday assumptions concerning the total behavior of a reasonable person.... An integrational linguistics must recognize that human beings inhabit a communicational space which is not neatly compartmentalized into language and nonlanguage.... It renounces in advance the possibility of setting up systems of forms and meanings which will "account for" a central core of linguistic behavior irrespective of the situation and communicational purposes involved. (Harris, 1981, p. 165)By innate [linguistic knowledge], Chomsky simply means "genetically programmed." He does not literally think that children are born with language in their heads ready to be spoken. He merely claims that a "blueprint is there, which is brought into use when the child reaches a certain point in her general development. With the help of this blueprint, she analyzes the language she hears around her more readily than she would if she were totally unprepared for the strange gabbling sounds which emerge from human mouths. (Aitchison, 1987, p. 31)Looking at ourselves from the computer viewpoint, we cannot avoid seeing that natural language is our most important "programming language." This means that a vast portion of our knowledge and activity is, for us, best communicated and understood in our natural language.... One could say that natural language was our first great original artifact and, since, as we increasingly realize, languages are machines, so natural language, with our brains to run it, was our primal invention of the universal computer. One could say this except for the sneaking suspicion that language isn't something we invented but something we became, not something we constructed but something in which we created, and recreated, ourselves. (Leiber, 1991, p. 8)Historical dictionary of quotations in cognitive science > Language
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9 Artificial Intelligence
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)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)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, EventuallyJust 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 ProgramMany 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)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)[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)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 FormThe 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)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)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)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)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 FormationIt 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)We might distinguish among four kinds of 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.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.... 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)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 ContextsEven 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)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)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 IntelligenceThe 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)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 PropositionsIn 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)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)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)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)Historical dictionary of quotations in cognitive science > Artificial Intelligence
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10 Bibliography
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Cambridge: Cambridge University Press.Historical dictionary of quotations in cognitive science > Bibliography
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11 Memory
To what extent can we lump together what goes on when you try to recall: (1) your name; (2) how you kick a football; and (3) the present location of your car keys? If we use introspective evidence as a guide, the first seems an immediate automatic response. The second may require constructive internal replay prior to our being able to produce a verbal description. The third... quite likely involves complex operational responses under the control of some general strategy system. Is any unitary search process, with a single set of characteristics and inputoutput relations, likely to cover all these cases? (Reitman, 1970, p. 485)[Semantic memory] Is a mental thesaurus, organized knowledge a person possesses about words and other verbal symbols, their meanings and referents, about relations among them, and about rules, formulas, and algorithms for the manipulation of these symbols, concepts, and relations. Semantic memory does not register perceptible properties of inputs, but rather cognitive referents of input signals. (Tulving, 1972, p. 386)The mnemonic code, far from being fixed and unchangeable, is structured and restructured along with general development. Such a restructuring of the code takes place in close dependence on the schemes of intelligence. The clearest indication of this is the observation of different types of memory organisation in accordance with the age level of a child so that a longer interval of retention without any new presentation, far from causing a deterioration of memory, may actually improve it. (Piaget & Inhelder, 1973, p. 36)4) The Logic of Some Memory Theorization Is of Dubious Worth in the History of PsychologyIf a cue was effective in memory retrieval, then one could infer it was encoded; if a cue was not effective, then it was not encoded. The logic of this theorization is "heads I win, tails you lose" and is of dubious worth in the history of psychology. We might ask how long scientists will puzzle over questions with no answers. (Solso, 1974, p. 28)We have iconic, echoic, active, working, acoustic, articulatory, primary, secondary, episodic, semantic, short-term, intermediate-term, and longterm memories, and these memories contain tags, traces, images, attributes, markers, concepts, cognitive maps, natural-language mediators, kernel sentences, relational rules, nodes, associations, propositions, higher-order memory units, and features. (Eysenck, 1977, p. 4)The problem with the memory metaphor is that storage and retrieval of traces only deals [ sic] with old, previously articulated information. Memory traces can perhaps provide a basis for dealing with the "sameness" of the present experience with previous experiences, but the memory metaphor has no mechanisms for dealing with novel information. (Bransford, McCarrell, Franks & Nitsch, 1977, p. 434)7) The Results of a Hundred Years of the Psychological Study of Memory Are Somewhat DiscouragingThe results of a hundred years of the psychological study of memory are somewhat discouraging. We have established firm empirical generalisations, but most of them are so obvious that every ten-year-old knows them anyway. We have made discoveries, but they are only marginally about memory; in many cases we don't know what to do with them, and wear them out with endless experimental variations. We have an intellectually impressive group of theories, but history offers little confidence that they will provide any meaningful insight into natural behavior. (Neisser, 1978, pp. 12-13)A schema, then is a data structure for representing the generic concepts stored in memory. There are schemata representing our knowledge about all concepts; those underlying objects, situations, events, sequences of events, actions and sequences of actions. A schema contains, as part of its specification, the network of interrelations that is believed to normally hold among the constituents of the concept in question. A schema theory embodies a prototype theory of meaning. That is, inasmuch as a schema underlying a concept stored in memory corresponds to the mean ing of that concept, meanings are encoded in terms of the typical or normal situations or events that instantiate that concept. (Rumelhart, 1980, p. 34)Memory appears to be constrained by a structure, a "syntax," perhaps at quite a low level, but it is free to be variable, deviant, even erratic at a higher level....Like the information system of language, memory can be explained in part by the abstract rules which underlie it, but only in part. The rules provide a basic competence, but they do not fully determine performance. (Campbell, 1982, pp. 228, 229)When people think about the mind, they often liken it to a physical space, with memories and ideas as objects contained within that space. Thus, we speak of ideas being in the dark corners or dim recesses of our minds, and of holding ideas in mind. Ideas may be in the front or back of our minds, or they may be difficult to grasp. With respect to the processes involved in memory, we talk about storing memories, of searching or looking for lost memories, and sometimes of finding them. An examination of common parlance, therefore, suggests that there is general adherence to what might be called the spatial metaphor. The basic assumptions of this metaphor are that memories are treated as objects stored in specific locations within the mind, and the retrieval process involves a search through the mind in order to find specific memories....However, while the spatial metaphor has shown extraordinary longevity, there have been some interesting changes over time in the precise form of analogy used. In particular, technological advances have influenced theoretical conceptualisations.... The original Greek analogies were based on wax tablets and aviaries; these were superseded by analogies involving switchboards, gramophones, tape recorders, libraries, conveyor belts, and underground maps. Most recently, the workings of human memory have been compared to computer functioning... and it has been suggested that the various memory stores found in computers have their counterparts in the human memory system. (Eysenck, 1984, pp. 79-80)Primary memory [as proposed by William James] relates to information that remains in consciousness after it has been perceived, and thus forms part of the psychological present, whereas secondary memory contains information about events that have left consciousness, and are therefore part of the psychological past. (Eysenck, 1984, p. 86)Once psychologists began to study long-term memory per se, they realized it may be divided into two main categories.... Semantic memories have to do with our general knowledge about the working of the world. We know what cars do, what stoves do, what the laws of gravity are, and so on. Episodic memories are largely events that took place at a time and place in our personal history. Remembering specific events about our own actions, about our family, and about our individual past falls into this category. With amnesia or in aging, what dims... is our personal episodic memories, save for those that are especially dear or painful to us. Our knowledge of how the world works remains pretty much intact. (Gazzaniga, 1988, p. 42)The nature of memory... provides a natural starting point for an analysis of thinking. Memory is the repository of many of the beliefs and representations that enter into thinking, and the retrievability of these representations can limit the quality of our thought. (Smith, 1990, p. 1)Historical dictionary of quotations in cognitive science > Memory
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12 structure
ˈstrʌktʃə сущ.
1) состав, строение, структура, устройство to generate a structure ≈ породить структуру, создать структуру deep structure molecular structure economic structure financial structure political structure power structure social structure surface structure tax structure wage structure Syn: wilful
2) дом, здание, сооружение, строение air structure структура - molecular * молекулярное строение (вещества) ;
структура /строение/ молекулы - the * of the atom структура атома - the * of society, social * общественный строй, социальная структура - the * of a language строй языка - complex * сложная структура - * anomaly аномалия структуры - * factor структурный фактор здание, сооружение, строение - a stately * величественное сооружение age ~ возрастной состав balance sheet ~ структура балансового отчета byte ~ вчт. байтовая структура case ~ вчт. развилка cognitive ~ вчт. когнитивная структура control ~ вчт. управляющая структура cost ~ структура издержек cost ~ структура себестоимости data ~ вчт. структура данных deep ~ вчт. глубинная структура directory ~ вчт. структура каталогов dot ~ вчт. точечная структура financial ~ финансовая структура( компании) herringbone ~ вчт. структура рыбий скелет homogeneous ~ вчт. однородная структура industrial ~ промышленное сооружение industrial ~ структура производства interest rate ~ структура ставки процента logical data ~ вчт. логическая структура данных management ~ структура управления market ~ рыночная структура nested ~ вчт. гнездовая структура network ~ вчт. сетевая структура occupational ~ структура занятости organization ~ организационная структура request ~ вчт. структура запроса ring ~ вчт. кольцевая структура ~ структура;
устройство;
social structure социальный строй;
the structure of a language строй языка;
the structure of a sentence структура предложения social ~ общественное устройство social ~ социальная структура storage ~ вчт. представление данных storage ~ comp. структура памяти structure здание, сооружение, строение ~ состав совокупности ~ структура, устройство ~ структура;
устройство;
social structure социальный строй;
the structure of a language строй языка;
the structure of a sentence структура предложения ~ структура ~ структурировать ~ устройство ~ структура;
устройство;
social structure социальный строй;
the structure of a language строй языка;
the structure of a sentence структура предложения ~ структура;
устройство;
social structure социальный строй;
the structure of a language строй языка;
the structure of a sentence структура предложения ~ of assets and capital структура активов и капитала ~ of costs структура затрат ~ of interest rates структура процентных ставок surface ~ вчт. поверхностная структура tree ~ древовидная структура tree ~ вчт. древовидная структура tripartite ~ трехсторонняя стуктура (органы, занимающихся трудовыми отношениями) underlying ~ вчт. глубинная структура user ~ вчт. контекст процесса wage ~ структура зарплатыБольшой англо-русский и русско-английский словарь > structure
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13 structure
[ˈstrʌktʃə]age structure возрастной состав balance sheet structure структура балансового отчета byte structure вчт. байтовая структура case structure вчт. развилка cognitive structure вчт. когнитивная структура control structure вчт. управляющая структура cost structure структура издержек cost structure структура себестоимости data structure вчт. структура данных deep structure вчт. глубинная структура directory structure вчт. структура каталогов dot structure вчт. точечная структура financial structure финансовая структура (компании) herringbone structure вчт. структура рыбий скелет homogeneous structure вчт. однородная структура industrial structure промышленное сооружение industrial structure структура производства interest rate structure структура ставки процента logical data structure вчт. логическая структура данных management structure структура управления market structure рыночная структура nested structure вчт. гнездовая структура network structure вчт. сетевая структура occupational structure структура занятости organization structure организационная структура request structure вчт. структура запроса ring structure вчт. кольцевая структура structure структура; устройство; social structure социальный строй; the structure of a language строй языка; the structure of a sentence структура предложения social structure общественное устройство social structure социальная структура storage structure вчт. представление данных storage structure comp. структура памяти structure здание, сооружение, строение structure состав совокупности structure структура, устройство structure структура; устройство; social structure социальный строй; the structure of a language строй языка; the structure of a sentence структура предложения structure структура structure структурировать structure устройство structure структура; устройство; social structure социальный строй; the structure of a language строй языка; the structure of a sentence структура предложения structure структура; устройство; social structure социальный строй; the structure of a language строй языка; the structure of a sentence структура предложения structure of assets and capital структура активов и капитала structure of costs структура затрат structure of interest rates структура процентных ставок surface structure вчт. поверхностная структура tree structure древовидная структура tree structure вчт. древовидная структура tripartite structure трехсторонняя стуктура (органы, занимающихся трудовыми отношениями) underlying structure вчт. глубинная структура user structure вчт. контекст процесса wage structure структура зарплаты -
14 Cerebral Action
I have devoted so much time to discussion of the problem of syntax not only because language is one of the most important products of human cerebral action, but also because the problems raised by the organization of language seem to me to be characteristic of almost all other cerebral activity. There is a series of hierarchies of organization; the order of vocal movements in pronouncing the words, the order of words in the sentence, the order of sentences in the paragraph, the rational order of paragraphs in a discourse. Not only speech, but all skilled acts seem to involve the same problems of serial ordering, even down to the temporal coordination of muscular contractions in such a movement as reaching and grasping. Analysis of the nervous mechanisms underlying order in the more primitive acts may contribute ultimately to the solution of even the physiology of logic. (Lashley, 1951, pp. 121-122)Historical dictionary of quotations in cognitive science > Cerebral Action
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15 Cognitive Science
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.... [P]eople and intelligent computers turn out to be merely different manifestations of the same underlying phenomenon. (Haugeland, 1981b, p. 31)2) Experimental Psychology, Theoretical Linguistics, and Computational Simulation of Cognitive Processes Are All Components of Cognitive ScienceI went away from the Symposium with a strong conviction, more intuitive than rational, that human experimental psychology, theoretical linguistics, and computer simulation of cognitive processes were all pieces of a larger whole, and that the future would see progressive elaboration and coordination of their shared concerns.... I have been working toward a cognitive science for about twenty years beginning before I knew what to call it. (G. A. Miller, 1979, p. 9)Cognitive Science studies the nature of cognition in human beings, other animals, and inanimate machines (if such a thing is possible). While computers are helpful within cognitive science, they are not essential to its being. A science of cognition could still be pursued even without these machines.Computer Science studies various kinds of problems and the use of computers to solve them, without concern for the means by which we humans might otherwise resolve them. There could be no computer science if there were no machines of this kind, because they are indispensable to its being. Artificial Intelligence is a special branch of computer science that investigates the extent to which the mental powers of human beings can be captured by means of machines.There could be cognitive science without artificial intelligence but there could be no artificial intelligence without cognitive science. One final caveat: In the case of an emerging new discipline such as cognitive science there is an almost irresistible temptation to identify the discipline itself (as a field of inquiry) with one of the theories that inspired it (such as the computational conception...). This, however, is a mistake. The field of inquiry (or "domain") stands to specific theories as questions stand to possible answers. The computational conception should properly be viewed as a research program in cognitive science, where "research programs" are answers that continue to attract followers. (Fetzer, 1996, pp. xvi-xvii)What is the nature of knowledge and how is this knowledge used? These questions lie at the core of both psychology and artificial intelligence.The psychologist who studies "knowledge systems" wants to know how concepts are structured in the human mind, how such concepts develop, and how they are used in understanding and behavior. The artificial intelligence researcher wants to know how to program a computer so that it can understand and interact with the outside world. The two orientations intersect when the psychologist and the computer scientist agree that the best way to approach the problem of building an intelligent machine is to emulate the human conceptual mechanisms that deal with language.... The name "cognitive science" has been used to refer to this convergence of interests in psychology and artificial intelligence....This working partnership in "cognitive science" does not mean that psychologists and computer scientists are developing a single comprehensive theory in which people are no different from machines. Psychology and artificial intelligence have many points of difference in methods and goals.... We simply want to work on an important area of overlapping interest, namely a theory of knowledge systems. As it turns out, this overlap is substantial. For both people and machines, each in their own way, there is a serious problem in common of making sense out of what they hear, see, or are told about the world. The conceptual apparatus necessary to perform even a partial feat of understanding is formidable and fascinating. (Schank & Abelson, 1977, pp. 1-2)Within the last dozen years a general change in scientific outlook has occurred, consonant with the point of view represented here. One can date the change roughly from 1956: in psychology, by the appearance of Bruner, Goodnow, and Austin's Study of Thinking and George Miller's "The Magical Number Seven"; in linguistics, by Noam Chomsky's "Three Models of Language"; and in computer science, by our own paper on the Logic Theory Machine. (Newell & Simon, 1972, p. 4)Historical dictionary of quotations in cognitive science > Cognitive Science
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16 UA
1) Общая лексика: Украина2) Компьютерная техника: Unnumbered Acknowledge, Unnumbered Acknowledgement3) Медицина: ОАМ, общий анализ мочи, общий клинический анализ мочи, общеклинический анализ мочи, clinical urine analysis, common urine analysis, common urine examination, clinical urine examination4) Американизм: Unified Agenda5) Спорт: Ultimate Adventure, Unreal Annihilation6) Военный термин: Un Authorized, Underground Area, Unit Attack, Unit Authorization, Universal Army, Universe Of Actions, Unlimited Ammo7) Техника: ultra-audible, ultrasonic attenuation, unauthorized absence, unipole antenna, unsafe action8) Юридический термин: User Authored9) Страхование: Underwriting account10) Грубое выражение: U Asshole11) Телекоммуникации: Universal Access, Unlimited Access, Unbalanced Asynchronous (HDLC), Unnumbered Acknowledgment (HDLC)12) Сокращение: United Artists, urbanized area, urinalysis, Harley-Davidson World War II 74 cubic inch V-twin military motorcycle model, Routine( pilot report message type), U'ltimos Adictos (Guatemala rock group), Ukraine (ISO Country Identifier), Ulkomaankaupan Agenttiliitto (Suomeksi) (Finnish Foreign Trade Agents' Federation, aka: FFTAF), Ultimate Adventures, Ultimate Adversaries (D20 Star Wars Roleplaying sourcebook), Unable to Approve Arrival for the Time Specified, Unaddressed, Unarmed (gaming), Unarmored (gaming), Unattended, Unauthorized Absence (Article 86 UCMJ), Unavailable, Unbalanced Asynchronous, Unbelievably Amazing, Und Andere (German: and others), Under Age, Under Armour (stock symbol), Underactive, Underground Atlanta, Underwriters Accepted, Unfair Advantage (CSI Data), Uniform Act (Uniform Relocation Assistance and Real Property Acquisitions Policies Act of 1970, as amended), Uniform Allowance, Unique Address, Unique Applications, Unit Administration, Unit Administrator (military term), Unit Area, Unit of Action, Unitary Authority (local government area, UK), United Airlines, United Association of Journeymen and Apprentices of the Plumbing and Pipe Fitting Industry of the United States and Canada (Union), Units of Account (banking), Universal Adversary, Universal Architecture, Universidad de Alicante (Spain), Universidade da Amazo^nia (Brasil), Universidade de Aveiro (Portugal), University Archives, University at Albany (SUNY), University of Aberdeen (UK), University of Akron (Ohio), University of Alabama, University of Alaska, University of Alberta, University of Antwerp, University of Arizona, University of Arkansas, University of California Audits, University of the Arctic, Unmanned Aircraft, Unmarried America, Unnecessary Acronym, Unnumbered Acknowledge (telecommunications), Unnumbered Acknowledgment, Unstable Angina, Unter Anderem (German: Among Other Things), Update Analysis, Upper Air, Upper Arlington (Ohio), Upper Arm, Uracil-Adenine (RNA base pairing), Urban Area, Urine Analysis, User Account, User Activity, User Agency, User Agent (web browser), User Agreement, User Assistance, User Authentication, Utility Accrual, Uto-Aztecan (language)13) Университет: The University Of Alabama, Undergraduate Association14) Физиология: Umbilical Artery, Uric Acid15) Вычислительная техника: user area, User Agent (MHS, OSI), Upgrade Advantage (MS)16) Банковское дело: соглашение о размещении ценных бумаг (underwriting agreement), расчётная единица (unit of account)17) Фирменный знак: Unlimited Adventures18) Деловая лексика: Underlying Asset, Union Avoidance, расчётная денежная единица (unit of account)19) Инвестиции: underwriting agreement, unit of account20) Сетевые технологии: абонентская служба, агент пользователя, пользовательский агент21) Программирование: Update Attribute22) Расширение файла: User Agent23) Должность: Undercover Agent, Undergraduate Assistant24) НАСА: Underground Access -
17 ua
1) Общая лексика: Украина2) Компьютерная техника: Unnumbered Acknowledge, Unnumbered Acknowledgement3) Медицина: ОАМ, общий анализ мочи, общий клинический анализ мочи, общеклинический анализ мочи, clinical urine analysis, common urine analysis, common urine examination, clinical urine examination4) Американизм: Unified Agenda5) Спорт: Ultimate Adventure, Unreal Annihilation6) Военный термин: Un Authorized, Underground Area, Unit Attack, Unit Authorization, Universal Army, Universe Of Actions, Unlimited Ammo7) Техника: ultra-audible, ultrasonic attenuation, unauthorized absence, unipole antenna, unsafe action8) Юридический термин: User Authored9) Страхование: Underwriting account10) Грубое выражение: U Asshole11) Телекоммуникации: Universal Access, Unlimited Access, Unbalanced Asynchronous (HDLC), Unnumbered Acknowledgment (HDLC)12) Сокращение: United Artists, urbanized area, urinalysis, Harley-Davidson World War II 74 cubic inch V-twin military motorcycle model, Routine( pilot report message type), U'ltimos Adictos (Guatemala rock group), Ukraine (ISO Country Identifier), Ulkomaankaupan Agenttiliitto (Suomeksi) (Finnish Foreign Trade Agents' Federation, aka: FFTAF), Ultimate Adventures, Ultimate Adversaries (D20 Star Wars Roleplaying sourcebook), Unable to Approve Arrival for the Time Specified, Unaddressed, Unarmed (gaming), Unarmored (gaming), Unattended, Unauthorized Absence (Article 86 UCMJ), Unavailable, Unbalanced Asynchronous, Unbelievably Amazing, Und Andere (German: and others), Under Age, Under Armour (stock symbol), Underactive, Underground Atlanta, Underwriters Accepted, Unfair Advantage (CSI Data), Uniform Act (Uniform Relocation Assistance and Real Property Acquisitions Policies Act of 1970, as amended), Uniform Allowance, Unique Address, Unique Applications, Unit Administration, Unit Administrator (military term), Unit Area, Unit of Action, Unitary Authority (local government area, UK), United Airlines, United Association of Journeymen and Apprentices of the Plumbing and Pipe Fitting Industry of the United States and Canada (Union), Units of Account (banking), Universal Adversary, Universal Architecture, Universidad de Alicante (Spain), Universidade da Amazo^nia (Brasil), Universidade de Aveiro (Portugal), University Archives, University at Albany (SUNY), University of Aberdeen (UK), University of Akron (Ohio), University of Alabama, University of Alaska, University of Alberta, University of Antwerp, University of Arizona, University of Arkansas, University of California Audits, University of the Arctic, Unmanned Aircraft, Unmarried America, Unnecessary Acronym, Unnumbered Acknowledge (telecommunications), Unnumbered Acknowledgment, Unstable Angina, Unter Anderem (German: Among Other Things), Update Analysis, Upper Air, Upper Arlington (Ohio), Upper Arm, Uracil-Adenine (RNA base pairing), Urban Area, Urine Analysis, User Account, User Activity, User Agency, User Agent (web browser), User Agreement, User Assistance, User Authentication, Utility Accrual, Uto-Aztecan (language)13) Университет: The University Of Alabama, Undergraduate Association14) Физиология: Umbilical Artery, Uric Acid15) Вычислительная техника: user area, User Agent (MHS, OSI), Upgrade Advantage (MS)16) Банковское дело: соглашение о размещении ценных бумаг (underwriting agreement), расчётная единица (unit of account)17) Фирменный знак: Unlimited Adventures18) Деловая лексика: Underlying Asset, Union Avoidance, расчётная денежная единица (unit of account)19) Инвестиции: underwriting agreement, unit of account20) Сетевые технологии: абонентская служба, агент пользователя, пользовательский агент21) Программирование: Update Attribute22) Расширение файла: User Agent23) Должность: Undercover Agent, Undergraduate Assistant24) НАСА: Underground Access -
18 computer
1) компьютер; вычислительная машина; ЭВМ; вычислительное устройство; вычислитель; редк. процессор2) редк. счётная машина (см. тж calculator, machine)•- adaptive computer
- airborne computer
- all-applications computer
- all-purpose computer
- alternating-current analog computer
- analog computer
- analog-digital computer
- arbitrary sequence computer
- associative computer
- asynchronous computer
- automotive computer
- baby-sized computer
- back-end computer
- batch-oriented computer
- battery-operated computer
- binary computer
- binary-transfer computer
- board computer
- boutique computer
- brand-name computer
- breadboard computer
- buffered computer
- business computer
- business-oriented computer
- byte computer
- byte-organized computer
- byte-oriented computer
- cassette-based computer
- census computer
- central computer
- character-oriented computer
- chemical-based computer
- chess computer
- CISC computer
- commercial computer
- commodity computer
- communication computer
- communications oriented computer
- compatible computer
- complete-instruction-set computer
- concurrent computer
- consecutive computer
- consecutive sequence computer
- continuously acting computer
- control computer
- control flow computer
- correlation computer
- coupled computers
- cryogenic computer
- cryotron computer
- custom computer
- database computer
- data-flow computer
- decimal computer
- dedicated computer
- desk computer
- desk-size computer
- desk-top computer
- dialing set computer
- dial set computer
- digital computer
- direct execution computer
- direct-analogy computer
- direct-current computer
- diskless computer
- distributed logic computer
- drum computer
- dual-processor computer
- education computer
- electromechanical analog computer
- electronic tube computer
- electron tube computer
- electronic computer
- end-user computer
- ever-faster computer
- externally programmed computer
- fault-tolerant computer
- fifth-generation computer
- file computer
- first-generation computer
- fixed word-length computer
- fixed-point computer
- fixed-program computer
- flat screen computer
- floating-point computer
- fluid computer
- four-address computer
- fourth-generation computer
- fractional computer
- front-end computer
- gateway computer
- general-purpose computer
- giant computer
- giant-powered computer
- giant-scale computer
- giant-size computer
- gigacycle computer
- gigahertz computer
- guidance computer
- handheld computer
- high-end computer
- high-function computer
- high-level language computer
- high-level computer
- highly parallel computer
- high-performance computer
- high-speed computer
- hobby computer
- home banking computer
- home computer
- host computer
- hybrid computer
- IBM-compatible computer
- IC computer
- incompatible computer
- incremental computer
- industrial computer
- integrated circuit computer
- interface computer
- interim computer
- intermediate computer
- internally programmed computer
- Internet computer
- keyboard computer
- kid computer
- laptop computer
- large computer
- large-powered computer
- large-scale computer
- large-scale integration circuit computer
- large-size computer
- laser computer
- linkage computer
- local computer
- logical computer
- logic computer
- logic-controlled sequential computer
- logic-in-memory computer
- low-end computer
- low-profile computer
- low-speed computer
- LSI computer
- mainframe computer
- massively parallel computer
- master computer
- mechanical computer
- medium computer
- medium-powered computer
- medium-size computer
- medium-speed computer
- medium-to-large scale computer
- mediun-scale computer
- megacycle computer
- megahertz computer
- microprogrammable computer
- microwave computer
- mid-range computer
- molecular computer
- monoprocessor computer
- multiaddress computer
- multi-MIPS computer
- multiple-access computer
- multiple-user computer
- multiprocessor computer
- multiprogrammed computer
- multipurpose computer
- multiradix computer
- navigation computer
- net node computer
- networked computer
- N-node computer
- no-address computer
- node computer
- nonsequential computer
- nonstop computer
- non-von Neumann computer
- notebook computer
- object computer
- office computer
- off-the-shelf computer
- one-address computer
- one-and-half-address computer
- one-on-one computer
- one-purpose computer
- optical computer
- optical path computer
- original computer
- palm-size computer - parallel-processing computer
- parallel-serial computer
- parametric-electronic computer
- parametron computer
- pen-based computer
- pentop computer
- perihperal support computer
- peripheral computer
- personal computer
- pictorial computer
- pipeline computer
- plugboard computer
- plug-compatible computer
- plugged program computer
- pneumatic computer
- pocket computer
- Polish-string computer
- polynomial computer
- portable computer
- process control computer
- production control computer
- professional computer
- professional personal computer
- program-compatible computer
- program-controlled computer
- programmed computer
- punch-card computer
- rack-size computer
- radix two computer
- real-time computer
- recovering computer
- reduced instruction set computer
- reduction computer
- remote computer
- repetitive computer
- RISC computer
- satellite computer
- scientific computer
- second-generation computer
- secondhand computer
- self-adapting computer
- self-organizing computer
- self-programming computer
- self-repairing computer
- self-repair computer
- sensor-based computer
- sequence-controlled computer
- sequenced computer
- sequential computer
- serial computer
- service computer
- service-oriented computer
- SIMD computer
- simultaneous-operation computer
- simultaneous computer
- single-address computer
- single-board computer
- single-purpose computer
- single-user computer
- slave computer
- small computer
- small-powered computer
- small-scale computer
- small-size computer
- soft-compatible computer
- solid-state computer
- SOS computer
- source computer
- space computer
- spaceborne computer
- special-purpose computer
- special computer
- square-root computer
- stack-oriented computer
- standby computer
- statistical computer
- steering computer
- stored-program computer
- subscriber computer
- super computer
- superconductive computer
- superhigh-speed computer
- superpersonal computer
- superspeed computer
- supervisory computer
- switch-control computer
- switching computer
- symbolic computer
- synchronous computer
- synchronous tracking computer
- tagged computer
- talking computer
- target computer
- technical computer
- technical personal computer
- terminal computer
- terminal control computer
- ternary-transfer computer
- tessellated computer
- thermal computer
- thin-film memory computer
- third-generation computer
- three-address computer
- three-dimensional analog computer
- timeshared computer
- top level computer
- top-of-the-line computer
- toy computer
- training computer
- transformation computer
- transistorized computer
- transistor computer
- translating computer
- tridimensional analog computer
- trip computer
- truth-table computer
- Turing-type computer
- two-address computer
- ultrafast computer
- underlying computer
- user computer
- vacuum tube computer
- variable word-length computer
- very-high-speed computer
- video-and-cassette-based computer
- virtual computer
- von Neumann computer
- wearable computer
- weather computer
- wired-program computer
- word-oriented computer
- workgroup computer
- X-computer
- zero-address computerEnglish-Russian dictionary of computer science and programming > computer
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19 graph
1) граф2) график || строить график3) диаграмма || чертить диаграмму•- alternating composition graph - arbitrarily transversable graph - derived graph - doubly connected graph - doubly transitive graph - fully connected graph - locally countable graph - locally finite graph - locally restricted graph - log-log graph - partially labeled graph - partially orderable graph - progressively finite graph - regressively finite graph - strictly weak graph - strongly orientable graph - strongly regular graph - strongly rigid graph - strongly singular graph - strongly smooth graph - totally inductive graph - triangleless graph - triply transitive graph - uniquely intersectable graph - uniquely representable graph - weakly disconnected graph -
20 Consciousness
Consciousness is what makes the mind-body problem really intractable.... Without consciousness the mind-body problem would be much less interesting. With consciousness it seems hopeless. (T. Nagel, 1979, pp. 165-166)This approach to understanding sensory qualia is both theoretically and empirically motivated... [;] it suggests an effective means of expressing the allegedly inexpressible. The "ineffable" pink of one's current visual sensation may be richly and precisely expressed as a 95Hz/80Hz/80Hz "chord" in the relevant triune cortical system. The "unconveyable" taste sensation produced by the fabled Australian health tonic Vegamite might be poignantly conveyed as a 85/80/90/15 "chord" in one's four channeled gustatory system.... And the "indescribably" olfactory sensation produced by a newly opened rose might be quite accurately described as a 95/35/10/80/60/55 "chord" in some six-dimensional space within one's olfactory bulb. (P. M. Churchland, 1989, p. 106)One of philosophy's favorite facets of mentality has received scant attention from cognitive psychologists, and that is consciousness itself: fullblown, introspective, inner-world phenomenological consciousness. In fact if one looks in the obvious places... one finds not so much a lack of interest as a deliberate and adroit avoidance of the issue. I think I know why. Consciousness appears to be the last bastion of occult properties, epiphenomena, and immeasurable subjective states-in short, the one area of mind best left to the philosophers, who are welcome to it. Let them make fools of themselves trying to corral the quicksilver of "phenomenology" into a respectable theory. (Dennett, 1978b, p. 149)When I am thinking about anything, my consciousness consists of a number of ideas.... But every idea can be resolved into elements... and these elements are sensations. (Titchener, 1910, p. 33)A Darwin machine now provides a framework for thinking about thought, indeed one that may be a reasonable first approximation to the actual brain machinery underlying thought. An intracerebral Darwin Machine need not try out one sequence at a time against memory; it may be able to try out dozens, if not hundreds, simultaneously, shape up new generations in milliseconds, and thus initiate insightful actions without overt trial and error. This massively parallel selection among stochastic sequences is more analogous to the ways of darwinian biology than to the "von Neumann" serial computer. Which is why I call it a Darwin Machine instead; it shapes up thoughts in milliseconds rather than millennia, and uses innocuous remembered environments rather than noxious real-life ones. It may well create the uniquely human aspect of our consciousness. (Calvin, 1990, pp. 261-262)To suppose the mind to exist in two different states, in the same moment, is a manifest absurdity. To the whole series of states of the mind, then, whatever the individual, momentary successive states may be, I give the name of our consciousness.... There are not sensations, thoughts, passions, and also consciousness, any more than there is quadruped or animal, as a separate being to be added to the wolves, tygers, elephants, and other living creatures.... The fallacy of conceiving consciousness to be something different from the feeling, which is said to be its object, has arisen, in a great measure, from the use of the personal pronoun I. (T. Brown, 1970, p. 336)The human capacity for speech is certainly unique. But the gulf between it and the behavior of animals no longer seems unbridgeable.... What does this leave us with, then, which is characteristically human?.... t resides in the human capacity for consciousness and self-consciousness. (Rose, 1976, p. 177)[Human consciousness] depends wholly on our seeing the outside world in such categories. And the problems of consciousness arise from putting reconstitution beside internalization, from our also being able to see ourselves as if we were objects in the outside world. That is in the very nature of language; it is impossible to have a symbolic system without it.... The Cartesian dualism between mind and body arises directly from this, and so do all the famous paradoxes, both in mathematics and in linguistics.... (Bronowski, 1978, pp. 38-39)It seems to me that there are at least four different viewpoints-or extremes of viewpoint-that one may reasonably hold on the matter [of computation and conscious thinking]:A. All thinking is computation; in particular, feelings of conscious awareness are evoked merely by the carrying out of appropriate computations.B. Awareness is a feature of the brain's physical action; and whereas any physical action can be simulated computationally, computational simulation cannot by itself evoke awareness.C. Appropriate physical action of the brain evokes awareness, but this physical action cannot even be properly simulated computationally.D. Awareness cannot be explained by physical, computational, or any other scientific terms. (Penrose, 1994, p. 12)Historical dictionary of quotations in cognitive science > Consciousness
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