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performance+testing+tool

  • 1 инструмент тестирования производительности

    Универсальный русско-английский словарь > инструмент тестирования производительности

  • 2 evaluación

    f.
    1 evaluation, rating, review, assessment.
    2 evaluation, valuation, break-down.
    * * *
    1 evaluation, assessment
    2 EDUCACIÓN (acción) assessment; (examen) exam
    * * *
    noun f.
    evaluation, assessment
    * * *
    SF
    1) (=valoración) [de datos] evaluation; [de daños, pérdidas] assessment
    2) (Escol) (=acción) assessment; (=examen) test
    * * *
    a) (de daños, situación) assessment; (de datos, informes) evaluation, assessment
    b) (Educ) ( acción) assessment; (prueba, examen) test
    * * *
    = appraisal, assaying, assessing, assessment, evaluation, measurement, trial, rating, evaluation rating, post mortem [postmortem].
    Ex. The notice could contain the list of the poorest performers, based on the most recent set of appraisals.
    Ex. Suppose you have classified, by UDC, the document 'Select methods of metallurgical assaying', class number 669.9.
    Ex. Consequently, the skill of shopping around and assessing the cost-effectiveness of a supplier's goods and services is important for the librarian to develop.
    Ex. However, although the subject may be the primary consideration in the assessment of relevance, subject is not the only factor that determines whether a user wishes to be alerted to the existence of a document.
    Ex. There is an extensive theory of the evaluation of indexes and indexing, but regrettably there is not space to treat this topic at any length in this work.
    Ex. Here ' Measurement' is an action term, and so, the operator for an action term is assigned to ' Measurement'.
    Ex. The intention was to determine which department within each library has the responsibility for arranging trials of products.
    Ex. But the rater must not be afraid to give negative ratings.
    Ex. In order to make sure that no prejudice or bias influences an evaluation rating, the rating should be reviewed by the supervisor's supervisor -- the next person in the hierarchy.
    Ex. Survey research is used to determine what kind of post mortem appraisals companies undertake concerning their abandoned information systems development projects.
    ----
    * comisión de evaluación = review panel, review board.
    * comité de evaluación = review panel, review board, review committee.
    * de evaluación = evaluative.
    * estándar de evaluación = benchmark.
    * evaluación anónima = blind review.
    * evaluación comparativa = benchmarking.
    * evaluación continua = continuous assessment, formative evaluation.
    * evaluación crítica = critical evaluation.
    * evaluación cualitativa = qualitative evaluation.
    * evaluación cuantitativa = quantitative evaluation.
    * evaluación de la calidad = quality assessment.
    * evaluación de la colección = collection assessment, collection evaluation, collection analysis.
    * evaluación de la productividad = performance appraisal, performance review.
    * evaluación de la seguridad = safety evaluation.
    * evaluación de las necesidades económicas = means-testing, means test.
    * evaluación del avance realizado = progress evaluation.
    * evaluación del impacto en función del género = gender-impact assessment.
    * evaluación de los ingresos = means-testing, means test.
    * evaluación de los productos = product rating.
    * evaluación del personal = personnel evaluation.
    * evaluación del profesorado = faculty evaluation.
    * evaluación del rendimiento = performance appraisal, performance evaluation, performance measurement, performance review, performance rating.
    * evaluación de metales = metallurgical assaying.
    * evaluación de necesidades = needs assessment.
    * evaluación de procedimientos = process rating.
    * evaluación de procesos = process rating.
    * evaluación de productos = product rating.
    * evaluación de riesgos = risk assessment.
    * evaluación de sistemas = system(s) evaluation.
    * evaluación de usuario = user rating.
    * evaluación final = summative evaluation, final assessment.
    * evaluación iluminativa = illuminative evaluation.
    * evaluación interviniente = obtrusive evaluation.
    * evaluación intrusiva = obtrusive evaluation, obtrusive test.
    * evaluación no intrusiva = unobtrusive evaluation.
    * evaluación objetiva = objective evaluation.
    * evaluación por comparación = benchmarking.
    * evaluación por expertos = peer review, refereeing, peer reviewing.
    * evaluación por expertos abierta = open refereeing.
    * evaluación por expertos anónima = blind refereeing.
    * evaluación por pares = peer review, refereeing, peer reviewing.
    * evaluación por resultados obtenidos = outcomes assessment.
    * evaluación sin intervención del examinador = unobtrusive testing.
    * herramienta de evaluación = assessment tool, evaluation tool.
    * impreso de evaluación = evaluation form.
    * instrumento de evaluación = assessment tool, evaluation tool.
    * método de evaluación de un edificio en uso = post-occupancy evaluation method.
    * nueva evaluación = reappraisal.
    * para la evaluación de hipótesis = hypothesis-testing.
    * procedimiento de evaluación por expertos = refereeing procedure.
    * proceso de evaluación = review process, evaluation process.
    * realizar una evaluación = administer + evaluation.
    * sistema de evaluación = rating system.
    * sistema de evaluación anónima = double-blind.
    * sistema de evaluación por paresanónima = double-blind refereeing system.
    * someter a una evaluación por expertos doble = double referee.
    * test de evaluación = evaluative test.
    * * *
    a) (de daños, situación) assessment; (de datos, informes) evaluation, assessment
    b) (Educ) ( acción) assessment; (prueba, examen) test
    * * *
    = appraisal, assaying, assessing, assessment, evaluation, measurement, trial, rating, evaluation rating, post mortem [postmortem].

    Ex: The notice could contain the list of the poorest performers, based on the most recent set of appraisals.

    Ex: Suppose you have classified, by UDC, the document 'Select methods of metallurgical assaying', class number 669.9.
    Ex: Consequently, the skill of shopping around and assessing the cost-effectiveness of a supplier's goods and services is important for the librarian to develop.
    Ex: However, although the subject may be the primary consideration in the assessment of relevance, subject is not the only factor that determines whether a user wishes to be alerted to the existence of a document.
    Ex: There is an extensive theory of the evaluation of indexes and indexing, but regrettably there is not space to treat this topic at any length in this work.
    Ex: Here ' Measurement' is an action term, and so, the operator for an action term is assigned to ' Measurement'.
    Ex: The intention was to determine which department within each library has the responsibility for arranging trials of products.
    Ex: But the rater must not be afraid to give negative ratings.
    Ex: In order to make sure that no prejudice or bias influences an evaluation rating, the rating should be reviewed by the supervisor's supervisor -- the next person in the hierarchy.
    Ex: Survey research is used to determine what kind of post mortem appraisals companies undertake concerning their abandoned information systems development projects.
    * comisión de evaluación = review panel, review board.
    * comité de evaluación = review panel, review board, review committee.
    * de evaluación = evaluative.
    * estándar de evaluación = benchmark.
    * evaluación anónima = blind review.
    * evaluación comparativa = benchmarking.
    * evaluación continua = continuous assessment, formative evaluation.
    * evaluación crítica = critical evaluation.
    * evaluación cualitativa = qualitative evaluation.
    * evaluación cuantitativa = quantitative evaluation.
    * evaluación de la calidad = quality assessment.
    * evaluación de la colección = collection assessment, collection evaluation, collection analysis.
    * evaluación de la productividad = performance appraisal, performance review.
    * evaluación de la seguridad = safety evaluation.
    * evaluación de las necesidades económicas = means-testing, means test.
    * evaluación del avance realizado = progress evaluation.
    * evaluación del impacto en función del género = gender-impact assessment.
    * evaluación de los ingresos = means-testing, means test.
    * evaluación de los productos = product rating.
    * evaluación del personal = personnel evaluation.
    * evaluación del profesorado = faculty evaluation.
    * evaluación del rendimiento = performance appraisal, performance evaluation, performance measurement, performance review, performance rating.
    * evaluación de metales = metallurgical assaying.
    * evaluación de necesidades = needs assessment.
    * evaluación de procedimientos = process rating.
    * evaluación de procesos = process rating.
    * evaluación de productos = product rating.
    * evaluación de riesgos = risk assessment.
    * evaluación de sistemas = system(s) evaluation.
    * evaluación de usuario = user rating.
    * evaluación final = summative evaluation, final assessment.
    * evaluación iluminativa = illuminative evaluation.
    * evaluación interviniente = obtrusive evaluation.
    * evaluación intrusiva = obtrusive evaluation, obtrusive test.
    * evaluación no intrusiva = unobtrusive evaluation.
    * evaluación objetiva = objective evaluation.
    * evaluación por comparación = benchmarking.
    * evaluación por expertos = peer review, refereeing, peer reviewing.
    * evaluación por expertos abierta = open refereeing.
    * evaluación por expertos anónima = blind refereeing.
    * evaluación por pares = peer review, refereeing, peer reviewing.
    * evaluación por resultados obtenidos = outcomes assessment.
    * evaluación sin intervención del examinador = unobtrusive testing.
    * herramienta de evaluación = assessment tool, evaluation tool.
    * impreso de evaluación = evaluation form.
    * instrumento de evaluación = assessment tool, evaluation tool.
    * método de evaluación de un edificio en uso = post-occupancy evaluation method.
    * nueva evaluación = reappraisal.
    * para la evaluación de hipótesis = hypothesis-testing.
    * procedimiento de evaluación por expertos = refereeing procedure.
    * proceso de evaluación = review process, evaluation process.
    * realizar una evaluación = administer + evaluation.
    * sistema de evaluación = rating system.
    * sistema de evaluación anónima = double-blind.
    * sistema de evaluación por paresanónima = double-blind refereeing system.
    * someter a una evaluación por expertos doble = double referee.
    * test de evaluación = evaluative test.

    * * *
    1 (de daños, pérdidas, una situación) assessment; (de datos, informes) evaluation, assessment
    en la reunión se hizo evaluación de la situación económica de la empresa they assessed the company's financial situation at the meeting
    2 ( Educ) (acción) assessment; (prueba, examen) test
    Compuesto:
    continuous assessment
    * * *

     

    evaluación sustantivo femenino
    a) (de daños, situación) assessment;

    (de datos, informes) evaluation, assessment
    b) (Educ) ( acción) assessment;

    (prueba, examen) test
    evaluación sustantivo femenino
    1 evaluation: tardaremos unos días en completar la evaluación de los daños sufridos, it'll take a few days to fully assess the damage
    2 Educ test: mañana tenemos la segunda evaluación de matemáticas, we have our second maths test tomorrow
    ' evaluación' also found in these entries:
    Spanish:
    valoración
    - cotización
    English:
    appraisal
    - appreciation
    - assessment
    - evaluation
    - continuous
    * * *
    1. [valoración] evaluation, assessment;
    [de daños, pérdidas, riesgos] assessment;
    una primera evaluación de las estadísticas confirma que… a first assessment of the statistics confirms that…;
    realizaron una evaluación de los daños they assessed the damage;
    hacen evaluaciones periódicas del rendimiento de los trabajadores employees are given regular performance evaluations o appraisals;
    hizo una evaluación positiva de la situación he gave a positive assessment of the situation
    Com evaluación comparativa benchmarking;
    evaluación de impacto ambiental environmental impact assessment;
    evaluación de riesgos risk assessment
    2. Educ [acción] assessment;
    [examen] exam, test; [periodo] = division of school year, of which there may be three to five in total evaluación continua continuous assessment
    * * *
    f
    1 evaluation, assessment
    2 ( prueba) test
    * * *
    evaluación nf, pl - ciones : assessment, evaluation
    * * *
    evaluación n assessment

    Spanish-English dictionary > evaluación

  • 3 Herbert, Edward Geisler

    [br]
    b. 23 March 1869 Dedham, near Colchester, Essex, England
    d. 9 February 1938 West Didsbury, Manchester, England
    [br]
    English engineer, inventor of the Rapidor saw and the Pendulum Hardness Tester, and pioneer of cutting tool research.
    [br]
    Edward Geisler Herbert was educated at Nottingham High School in 1876–87, and at University College, London, in 1887–90, graduating with a BSc in Physics in 1889 and remaining for a further year to take an engineering course. He began his career as a premium apprentice at the Nottingham works of Messrs James Hill \& Co, manufacturers of lace machinery. In 1892 he became a partner with Charles Richardson in the firm of Richardson \& Herbert, electrical engineers in Manchester, and when this partnership was dissolved in 1895 he carried on the business in his own name and began to produce machine tools. He remained as Managing Director of this firm, reconstituted in 1902 as a limited liability company styled Edward G.Herbert Ltd, until his retirement in 1928. He was joined by Charles Fletcher (1868–1930), who as joint Managing Director contributed greatly to the commercial success of the firm, which specialized in the manufacture of small machine tools and testing machinery.
    Around 1900 Herbert had discovered that hacksaw machines cut very much quicker when only a few teeth are in operation, and in 1902 he patented a machine which utilized this concept by automatically changing the angle of incidence of the blade as cutting proceeded. These saws were commercially successful, but by 1912, when his original patents were approaching expiry, Herbert and Fletcher began to develop improved methods of applying the rapid-saw concept. From this work the well-known Rapidor and Manchester saws emerged soon after the First World War. A file-testing machine invented by Herbert before the war made an autographic record of the life and performance of the file and brought him into close contact with the file and tool steel manufacturers of Sheffield. A tool-steel testing machine, working like a lathe, was introduced when high-speed steel had just come into general use, and Herbert became a prominent member of the Cutting Tools Research Committee of the Institution of Mechanical Engineers in 1919, carrying out many investigations for that body and compiling four of its Reports published between 1927 and 1933. He was the first to conceive the idea of the "tool-work" thermocouple which allowed cutting tool temperatures to be accurately measured. For this advance he was awarded the Thomas Hawksley Gold Medal of the Institution in 1926.
    His best-known invention was the Pendulum Hardness Tester, introduced in 1923. This used a spherical indentor, which was rolled over, rather than being pushed into, the surface being examined, by a small, heavy, inverted pendulum. The period of oscillation of this pendulum provided a sensitive measurement of the specimen's hardness. Following this work Herbert introduced his "Cloudburst" surface hardening process, in which hardened steel engineering components were bombarded by steel balls moving at random in all directions at very high velocities like gaseous molecules. This treatment superhardened the surface of the components, improved their resistance to abrasion, and revealed any surface defects. After bombardment the hardness of the superficially hardened layers increased slowly and spontaneously by a room-temperature ageing process. After his retirement in 1928 Herbert devoted himself to a detailed study of the influence of intense magnetic fields on the hardening of steels.
    Herbert was a member of several learned societies, including the Manchester Association of Engineers, the Institute of Metals, the American Society of Mechanical Engineers and the Institution of Mechanical Engineers. He retained a seat on the Board of his company from his retirement until the end of his life.
    [br]
    Principal Honours and Distinctions
    Manchester Association of Engineers Butterworth Gold Medal 1923. Institution of Mechanical Engineers Thomas Hawksley Gold Medal 1926.
    Bibliography
    E.G.Herbert obtained several British and American patents and was the author of many papers, which are listed in T.M.Herbert (ed.), 1939, "The inventions of Edward Geisler Herbert: an autobiographical note", Proceedings of the Institution of Mechanical Engineers 141: 59–67.
    ASD / RTS

    Biographical history of technology > Herbert, Edward Geisler

  • 4 руководство


    manual, handbook
    (инструкция)
    - для членов экипажа (по отысканию неисправностей и памятка экипажу) — flight crew operating manual
    - по аэродромному обслуживанию — air terminal handbook
    - no аэродромному и наземному оборудованию — ground equipment manual
    - по донесениям о неисправностях — fault report manual
    - по загрузке и центровке — weight and balance manual
    - по инструменту и оборудованию (иллюстрированное) — illustrated tool and equipment manual
    - по летной эксплуатации (самолета) — (airplane) flight manual (afm)
    рлэ должно содержать cледующие основные разделы: — the manual should be divided into sections as follows:
    1. общие сведения — 1. general
    2. ограничения — 2. limitations
    3. эксплуатация в аварийных условиях — 3. emergency procedures
    4. эксплуатация в нормальных условиях — 4. normal procedures
    5. летные характеристики — 5. performance appendices (if necessary)
    - по монтажу силовой установки — power plant built-up manual (ata-10o, 2-10-0)
    - по неразрушающему контролю (по неразрущающим методам контроля) — nondestructive testing manual
    - по обслуживанию (самолета) в ангарах, мастерских — facility planning manual
    - по представлению данных об авиационных происшествиях и предпосылках к ним — accident/incident data reporting (adrep)
    - по производству полетов для летчиков-любителей — private pilots' flight learning guide
    - (по капитальному) ремонту — overhaul manual
    руководство по ремонту содержит информацию описательного характера, а также конкретные сведения и порядок операций по ремонту изделий и узлов, демонтированных с ла. обычно рр подготавливается для механиков ремонтных мастерских. — the overhaul manual contains overhaul instructions containing descriptive information and specific procedures and data pertaining to work done on units and assemblies removed from the aircraft. they are normally prepared for the mechanic who performs shop work.
    pp состоит из следующих разделов: описание и принцип действия, (приемка в ремонт), разборка, очистка и промывка, дефектация (определение технического состояния деталей), ремонт, сборка, допуски и посадки, испытания (проверка), устранение неисправностей, храненце (консервация, упаковка, маркировка). — overhaul manual sections description and operation, (acceptance for overhaul), disassembly, cleaning, inspection/check, repair, assembly, testing, fits and clearances, troubleshooting, storage instructions, special tools, fixtures, and equipment, illustrated parts list.
    - по ремонту планера руководство, подготавливаемое изготовителем планера ла, должно содержать сведения описательного характара, конкретные указания и данные по ремонту силового набора и вспомогательных узлов планера применительно к ремонту в аэродромных условиях. — structural repair manual the manufacturer's structural repair manual shall contain descriptive information and specific instructions and data pertaining to the repair of the primary and secondary structure adaptable to field repair.
    - по окончательной сборке силовой установки (по оснащению собственно двигателя агрегатами и наружными узлами и деталями) — power plant build-up manual the power plant build-up manual shall contain all information necessary to assemble the power plant to the desired configuration from the "basic engine".
    - по технической эксплуатации руководство включает следующие основные главы: описание и работа (или принцип действия), отыскание и устранение неисправностей и инструкции по эксплуатации. — maintenance manual the maintenance manual contains: description and operation, trouble shooting and maintenance practices.
    инструкция по эксплуатации включает: обслуживание, демонтаж /монтаж, регулировка/испытание,осмотр/проверка, очистка/окраска, текущий ремонт. — the maintenance practices cover: servicing, removal/installation, adjustment/test, inspection/cheek,cleaning/painting, approved repairs.
    - по транспортировочным возможностям ла — (aircraft) transportability manual
    - по устранению неисправностей (ла) — aircraft) retrieval manual
    - по эксплуатации (техническому обслуживанию) — maintenance manual
    - по эксплуатации (с указанием правил работы с изделием или оборудованием) — operation and maintenance manual
    - по эксплуатации блоков (входящих в систему) — components maintenance manual
    - по эксплуатации грузового (погрузочного) оборудования — cargo systems operations manual
    - по эксплуатации наземного оборудования — ground equipment operation and maintenance manual
    - предназначено (написано) для обучения летчика метолам эксплуатации (оборудования) — manual is written to instruct the pilot in operation (of equipment)
    - с упрощенными (принципиальными) схемами — schematics manual

    Русско-английский сборник авиационно-технических терминов > руководство

  • 5 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, Eventually
       Just as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)
       Many problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)
       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 Form
       The basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)
       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 Formation
       It is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)
       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 Contexts
       Even if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)
       Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)
        18) The Assumption That the Mind Is a Formal System
       Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)
        19) A Statement of the Primary and Secondary Purposes of Artificial Intelligence
       The primary goal of Artificial Intelligence is to make machines smarter.
       The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)
       The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....
       AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)
        21) Perceptual Structures Can Be Represented as Lists of Elementary Propositions
       In artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)
       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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