-
1 abstract data types
Программирование: абстрактные типы данных -
2 data model
"A collection of related object types, operators, and integrity rules that form the abstract entity supported by a database management system (DBMS). Thus, one speaks of a relational DBMS, a network DBMS, and so on, depending on the type of data model a DBMS supports. In general, a DBMS supports only one data model as a practical rather than a theoretical restriction." -
3 ADT
1) Медицина: any what you desire thing (сокр.) (всё, что угодно (указание врача-диетолога)), androgen deprivation therapy2) Американизм: Administrative Decisions Tribunal3) Военный термин: Additional Duty Training, Alaskan daylight time, Assistant Director of Training, Assistant Director of Transportation, Automatic Digital Tester, Automatic Double Tracking, accelerated development test, active duty for training, actual departure time, advanced design team, advanced development technology, aided tracking, air data terminal, approved departure time, atomic damage template, automated data transmission, automatic detection and tracking, average daily traffic, amphibious training demonstrator( сокр.) (наглядное пособие по отработке морских десантных операций)4) Техника: accelerated development tests, aerated drain tank, air data transducer, airborne digital timer, alloy diffusion technique, automatic detector and tracker, available device table5) Шутливое выражение: A Daft Tosser, Americas Dumbest Technicians6) Сокращение: Advanced Display Terminal, Air Defence Technology programme, Air Detection and Tracking, Airborne Data Terminal, Alphanumeric Display Terminal, Automatic Data Transmission, Automatic Detection & Tracking, Application Design Tool, типы прикладных данных (Application Data Types), American District Telegraph Company («Америкэн дистрикт телеграф компани» (наименование американкой телеграфной компании)), actual drilling time8) Электроника: Applied diagnostic techniques10) Вычислительная техника: Address-Data Transceiver, Application Data Type, Atlantic Daylight Time, abstract data types, architecture definition technique, Atlantic Daylight Time (-0300, TZ, AST), Application Development Tools (IBM, AS/400), Access Developer's Toolkit (MS, DB, Windows), abstract data type11) Нефть: alloy-diffusion technique, applied drilling technology, articulated dump truck, применяемая технология бурения (applied drilling technology)12) Транспорт: Average Daily Trips13) Фирменный знак: American District Telegraph14) СМИ: Accumulated Delay Transcription15) Бурение: технология практического бурения (applied drilling technology)16) Полимеры: automatic data translator17) Расширение файла: AdTech Fax document, Admission Discharge and Transfer, Application Data Types, HP NewWave Cardfile Application Datafile, Dictionary (Lingvo)18) Общественная организация: American Discovery Trail -
4 ADt
1) Медицина: any what you desire thing (сокр.) (всё, что угодно (указание врача-диетолога)), androgen deprivation therapy2) Американизм: Administrative Decisions Tribunal3) Военный термин: Additional Duty Training, Alaskan daylight time, Assistant Director of Training, Assistant Director of Transportation, Automatic Digital Tester, Automatic Double Tracking, accelerated development test, active duty for training, actual departure time, advanced design team, advanced development technology, aided tracking, air data terminal, approved departure time, atomic damage template, automated data transmission, automatic detection and tracking, average daily traffic, amphibious training demonstrator( сокр.) (наглядное пособие по отработке морских десантных операций)4) Техника: accelerated development tests, aerated drain tank, air data transducer, airborne digital timer, alloy diffusion technique, automatic detector and tracker, available device table5) Шутливое выражение: A Daft Tosser, Americas Dumbest Technicians6) Сокращение: Advanced Display Terminal, Air Defence Technology programme, Air Detection and Tracking, Airborne Data Terminal, Alphanumeric Display Terminal, Automatic Data Transmission, Automatic Detection & Tracking, Application Design Tool, типы прикладных данных (Application Data Types), American District Telegraph Company («Америкэн дистрикт телеграф компани» (наименование американкой телеграфной компании)), actual drilling time8) Электроника: Applied diagnostic techniques10) Вычислительная техника: Address-Data Transceiver, Application Data Type, Atlantic Daylight Time, abstract data types, architecture definition technique, Atlantic Daylight Time (-0300, TZ, AST), Application Development Tools (IBM, AS/400), Access Developer's Toolkit (MS, DB, Windows), abstract data type11) Нефть: alloy-diffusion technique, applied drilling technology, articulated dump truck, применяемая технология бурения (applied drilling technology)12) Транспорт: Average Daily Trips13) Фирменный знак: American District Telegraph14) СМИ: Accumulated Delay Transcription15) Бурение: технология практического бурения (applied drilling technology)16) Полимеры: automatic data translator17) Расширение файла: AdTech Fax document, Admission Discharge and Transfer, Application Data Types, HP NewWave Cardfile Application Datafile, Dictionary (Lingvo)18) Общественная организация: American Discovery Trail -
5 adt
1) Медицина: any what you desire thing (сокр.) (всё, что угодно (указание врача-диетолога)), androgen deprivation therapy2) Американизм: Administrative Decisions Tribunal3) Военный термин: Additional Duty Training, Alaskan daylight time, Assistant Director of Training, Assistant Director of Transportation, Automatic Digital Tester, Automatic Double Tracking, accelerated development test, active duty for training, actual departure time, advanced design team, advanced development technology, aided tracking, air data terminal, approved departure time, atomic damage template, automated data transmission, automatic detection and tracking, average daily traffic, amphibious training demonstrator( сокр.) (наглядное пособие по отработке морских десантных операций)4) Техника: accelerated development tests, aerated drain tank, air data transducer, airborne digital timer, alloy diffusion technique, automatic detector and tracker, available device table5) Шутливое выражение: A Daft Tosser, Americas Dumbest Technicians6) Сокращение: Advanced Display Terminal, Air Defence Technology programme, Air Detection and Tracking, Airborne Data Terminal, Alphanumeric Display Terminal, Automatic Data Transmission, Automatic Detection & Tracking, Application Design Tool, типы прикладных данных (Application Data Types), American District Telegraph Company («Америкэн дистрикт телеграф компани» (наименование американкой телеграфной компании)), actual drilling time8) Электроника: Applied diagnostic techniques10) Вычислительная техника: Address-Data Transceiver, Application Data Type, Atlantic Daylight Time, abstract data types, architecture definition technique, Atlantic Daylight Time (-0300, TZ, AST), Application Development Tools (IBM, AS/400), Access Developer's Toolkit (MS, DB, Windows), abstract data type11) Нефть: alloy-diffusion technique, applied drilling technology, articulated dump truck, применяемая технология бурения (applied drilling technology)12) Транспорт: Average Daily Trips13) Фирменный знак: American District Telegraph14) СМИ: Accumulated Delay Transcription15) Бурение: технология практического бурения (applied drilling technology)16) Полимеры: automatic data translator17) Расширение файла: AdTech Fax document, Admission Discharge and Transfer, Application Data Types, HP NewWave Cardfile Application Datafile, Dictionary (Lingvo)18) Общественная организация: American Discovery Trail -
6 type
1) типа) класс; категория; родб) группа; вид2) модель; образец || быть моделью; служить образцом3) вчт символ ( определённого типа) || служить символом4) литера5) шрифт7) печатать (напр. на пишущей машине); набирать (напр. текст); вводить (напр. данные)8) распечатывать (напр. файл); выводить (напр. данные)•- type of entity
- abstract data type
- acoustical type of lattice vibration
- algebraic data type
- application-oriented data type
- body type
- built-in type
- condensed type
- conductivity type
- constructed data type
- creator type
- data type
- derived type
- digitized type
- display type
- emission type
- encapsulated type
- enumerated type
- expanded type
- fundamental type
- generic type
- immutable reference type
- integral type
- large resource data type
- memory type
- MIME type
- mode type
- Moon type
- mutable reference type
- optical type of lattice vibration
- ordinal type
- parametrized type
- portable user type
- predefined type
- preferred types
- primary type
- primitive type
- private type
- reference type
- resource type
- restricted type
- rotated type
- scalar data type
- set type
- small resource data type
- spectral type
- sum of product type
- user-defined type
- vector data type
- wraparound type -
7 type
taɪp
1. сущ.
1) тип;
представитель, образчик Have you done this type of work before? ≈ Вы уже делали такого рода работу?
2) класс, род Syn: kind, sort
3) модель
4) полигр. литера;
шрифт to set type ≈ набирать шрифт to set type by hand ≈ набирать шрифт вручную black type, bold type, boldface type, boldfaced type, fat type ≈ жирный шрифт elite type ≈ шрифт пишущей машинки в 12 знаков на дюйм;
цицеро italic type ≈ наклонный шрифт, курсив pica type ≈ цицеро regular type ≈ нормальный, базовый шрифт Roman type ≈ шрифт с засечами font of type ≈ шрифт, комплект шрифта fount of type ≈ шрифт, комплект шрифта, гарнитура
2. прил.
1) типографский type page ≈ полоса набора
2) типичный
3. гл.
1) писать, печатать на машинке to type a letter ≈ напечатать на машинке письмо She types well. ≈ Она печатает хорошо.
2) определять;
классифицировать;
относить к определенному типу to type a blood sample ≈ определять группу крови
3) быть типичным представителем
4) служить прообразом, быть прототипом;
предвосхищать ∙ type in typeout тип, типичный образец или представитель (чего-либо) - true to * типичный, характерный разновидность - literary * литературный тип род, класс, группа - blood * группа крови - seedless * of orange бессемянный сорт апельсина символ;
эмблема - a * of what was to come символ того, что должно было произойти модель, образец( в искусстве) - a * of Italian beauty тип итальянской красоты изображение на монете или медали отличительный знак или отличительная метка;
водяной знак - to be of the same * иметь один и тот же отличительный знак штамп, оттиск (полиграфия) литера (полиграфия) шрифт - black * жирный шрифт набор - cold * холодный набор (машинописный набор для фотоофсетного размножения) типичный типографский - * composition типографский набор писать, печатать на машинке - to * a letter напечатать на машинке письмо определять - to * a blood sample (медицина) определять группу крови классифицировать;
относить к определенному типу - she *d him a hero она отнесла его к разряду героев быть типичным представителем служить прообразом, быть прототипом;
предвосхищать (театроведение) подбирать актеров на роли по принципу типажности (театроведение) занимать актера в однотипных ролях abstract data ~ вчт. абстрактный тип данных aggregate ~ вчт. составной тип average ~ тип убытков base ~ вчт. исходный тип ~ полигр. литера;
шрифт;
black( или bold, fat) type жирный шрифт blocking ~ вчт. непрозрачный тип ~ род, класс, группа;
blood type группа крови body ~ полигр. шрифт основного текста boldfaced ~ полигр. выделительный шрифт boldfaced ~ полигр. жирный шрифт built-in ~ вчт. встроенный тип cold ~ вчт. компьютерный набор текста cold ~ машинописный набор cold ~ полигр. фотонабор cold ~ фотонабор cost ~ вид издержек data ~ вчт. тип данных device ~ вчт. тип устройства encapsulated ~ вчт. скрытый тип enumerated ~ вчт. перечислимый тип field ~ вчт. тип поля file ~ вчт. тип файла floating-point ~ вчт. тип с плавающей точкой fundamental data ~ вчт. основной тип данных fundamental ~ вчт. основной тип данных handling ~ вчт. вид обработки heavy-face ~ полигр. жирный шрифт investment ~ тип инвестирования jukebox ~ вчт. с автоматической сменой дисков media ~ вчт. тип носителя member ~ вчт. тип члена mixing ~ вчт. смешанный тип operation ~ вчт. вид операции ordinal ~ вчт. перечислимый тип poison ~ третий класс predefined ~ вчт. предопределенный тип primary ~ вчт. простой тип prime ~ вчт. простой тип private ~ вчт. приватный тип procedural ~ вчт. процедурный тип proportional ~ вчт. пропорциональный шрифт record ~ вчт. тип записи restricted ~ вчт. ограниченный тип scalar ~ вчт. скалярный тип set ~ вчт. тип набора statement ~ вчт. вид оператора ~ тип;
типичный образец или представитель (чего-л.) ;
true to type типичный;
характерный type вид ~ изображение на монете или медали ~ категория ~ класс ~ вчт. класс ~ полигр. литера;
шрифт;
black (или bold, fat) type жирный шрифт ~ полигр. литера ~ модель, образец;
символ ~ напечатать ~ печатать ~ писать на машинке ~ разновидность ~ род, класс, группа;
blood type группа крови ~ род ~ тип;
типичный образец или представитель (чего-л.) ;
true to type типичный;
характерный ~ тип ~ типичный образец ~ полигр. шрифт ~ attr.: ~ page полоса набора ~ in вчт. впечатать ~ in вчт. впечатывать ~ of account разновидность счета ~ of company тип компании ~ of enterprise тип предприятия ~ of expenditure категория затрат ~ of expenditure statement форма сметной калькуляции ~ of goods категория товаров ~ of goods товарная группа ~ of income вид дохода ~ of insurance вид страхования ~ of liability форма ответственности ~ of wages форма оплаты труда ~ attr.: ~ page полоса набора user-defined ~ вчт. тип пользователя variable ~ вчт. тип переменной -
8 module
"In programming, a collection of routines and data structures that performs a particular task or implements a particular abstract data type. Modules usually consist of two parts: an interface, which lists the constants, data types, variables, and routines that can be accessed by other modules or routines, and an implementation, which is private (accessible only to the module) and which contains the source code that actually implements the routines in the module." -
9 type
3) шрифт4) писать [печатать\] на пишущей машине5) вчт. вводить( с клавиатуры), набирать ( на клавиатуре)•-
abstract data type
-
access type
-
acoustical type of lattice vibration
-
advertizing type
-
aggregate type
-
arabic type
-
array type
-
base type
-
body type
-
bold-face type
-
bold type
-
book type
-
built-in type
-
capital type
-
character type
-
cold type
-
condensed type
-
conduction type
-
data type
-
derived type
-
display type
-
elite type
-
encapsulated type
-
enumerated type
-
first type of occurrence
-
fixed-point type
-
fixed type
-
floating-point type
-
floating type
-
generic type
-
integer type
-
interchangeable type
-
italic type
-
light type
-
lower case type
-
medium type
-
model type
-
optical type of lattice vibration
-
ordinary spacing type
-
own type
-
owner type
-
packed type
-
part type
-
pica type
-
playback type of operation
-
predefined type
-
primary type
-
printing type
-
proportional spacing type
-
record type
-
restricted type
-
reverse type
-
roman type
-
scalar type
-
script type
-
second type of occurrence
-
set type
-
task type
-
text type
-
transfer type
-
truck body type
-
truck chassis type
-
type of a distribution
-
type of growth
-
type of iron
-
types of wear
-
typewriter type
-
vacuous type
-
variable type -
10 geography
An abstract data type that is the base type for all geospatial data types in ellipsoidal coordinate systems. -
11 geometry
An abstract data type that is the base type for all geospatial data types in planar coordinate systems. -
12 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
-
13 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
См. также в других словарях:
Abstract data type — In computing, an abstract data type (ADT) is a specification of a set of data and the set of operations that can be performed on the data. Such a data type is abstract in the sense that it is independent of various concrete implementations. The… … Wikipedia
Data integration — involves combining data residing in different sources and providing users with a unified view of these data.[1] This process becomes significant in a variety of situations, which include both commercial (when two similar companies need to merge… … Wikipedia
Data virtualization — describes the process of abstracting disparate data sources (databases, applications, file repositories, websites, data services vendors, etc.) through a single data access layer (which may be any of several data access mechanisms). This… … Wikipedia
Data type — For other uses, see Data type (disambiguation). In computer programming, a data type is a classification identifying one of various types of data, such as floating point, integer, or Boolean, that determines the possible values for that type; the … Wikipedia
Data model — Overview of data modeling context: A data model provides the details of information to be stored, and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional… … Wikipedia
Abstract type — This article discusses types with no direct members; see also Abstract data type. In software engineering, an abstract type is a type in a nominative type system which is declared by the programmer, and which has the property that it contains no… … Wikipedia
Data structure — In computer science, a data structure is a particular way of storing and organizing data in a computer so that it can be used efficiently.[1][2] Different kinds of data structures are suited to different kinds of applications, and some are highly … Wikipedia
Data mining — Not to be confused with analytics, information extraction, or data analysis. Data mining (the analysis step of the knowledge discovery in databases process,[1] or KDD), a relatively young and interdisciplinary field of computer science[2][3] is… … Wikipedia
Abstract syntax — The abstract syntax of data is its structure described as a data type (possibly, but not necessarily, an abstract data type), independent of any particular representation or encoding. To be implemented either for computation or communications, a… … Wikipedia
Data access object — This article is about the data access object design pattern in object oriented software design. For the Microsoft library of the same name, see Data Access Objects. In computer software, a data access object (DAO) is an object that provides an… … Wikipedia
Data Access Object — This article is about the Data Access Object design pattern in object oriented software design, not about the Data Access Objects library from Microsoft. In computer software, a Data Access Object (DAO) is an object that provides an abstract… … Wikipedia
