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    Wyświetlanie 1-2 z 2
    Tytuł:
    O różnych sposobach rozumienia analogowości w informatyce
    Autorzy:
    Stacewicz, Paweł
    Powiązania:
    https://bibliotekanauki.pl/articles/429157.pdf
    Data publikacji:
    2017
    Wydawca:
    Uniwersytet Papieski Jana Pawła II w Krakowie
    Tematy:
    continuous computations
    analog computations
    analogicity
    GPAC model
    Turing machine
    natural computing
    hypercomputations
    computability
    Opis:
    Two different types of analog computations are discussed in the paper: 1)analog-continuous computations (performed physically upon continuous signals),2) analog-analogical computations (performed naturally by means of socalled natural analogons of mathematical operations). They are analyzed withregard to such questions like: a) are continuous computations physically implementable?b) what is the actual computational power of different analogtechniques? c) can natural (empirical) computations be such reliable as digital?d) is it possible to develop universal analog computers (assuming that theyshould be functionally similar to universal Turing machine)? Presented analysesare rather methodological than formal.
    Źródło:
    Semina Scientiarum; 2017, 16
    1644-3365
    Pojawia się w:
    Semina Scientiarum
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The Computational and Pragmatic Approach to the Dynamics of Science
    Autorzy:
    Marciszewski, Witold
    Powiązania:
    https://bibliotekanauki.pl/articles/41310393.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Instytut Filozofii i Socjologii PAN
    Tematy:
    algorithm
    behavioral (vs declarative) knowledge
    computability
    corroboration
    innate knowledge
    intuition
    invention
    logic gates
    oracle
    pragmatic (vs classical) rationalism
    problem-solving
    reasoning
    symbolic logic
    Turing machine
    Opis:
    Science means here mathematics and those empirical disciplines which avail themselves of mathematical models. The pragmatic approach is conceived in Karl R. Popper’s The Logic of Scientific Discovery (p. 276) sense: a logical appraisal of the success of a theory amounts to the appraisal of its corroboration. This kind of appraisal is exemplified in section 6 by a case study—on how Isaac Newton justified his theory of gravitation. The computational approach in problem-solving processes consists in considering them in terms of computability: either as being performed according to a model of computation in a narrower sense, e.g., the Turing machine, or in a wider perspective—of machines associated with a non-mechanical device called “oracle” by Alan Turing (1939). Oracle can be interpreted as computertheoretic representation of intuition or invention. Computational approach in another sense means considering problem-solving processes in terms of logical gates, supposed to be a physical basis for solving problems with a reasoning. Pragmatic rationalism about science, seen at the background of classical rationalism (Descartes, Gottfried Leibniz etc.), claims that any scientific idea, either in empirical theories or in mathematics, should be checked through applications to problem-solving processes. Both the versions claim the existence of abstract objects, available to intellectual intuition. The difference concerns the dynamics of science: (i) the classical rationalism regards science as a stationary system that does not need improvements after having reached an optimal state, while (ii) the pragmatical version conceives science as evolving dynamically due to fertile interactions between creative intuitions, or inventions, with mechanical procedures. The dynamics of science is featured with various models, like Derek J. de Solla Price’s exponential and Thomas Kuhn’s paradigm model (the most familiar instances). This essay suggests considering Turing’s idea of oracle as a complementary model to explain most adequately, in terms of exceptional inventiveness, the dynamics of mathematics and mathematizable empirical sciences.
    Źródło:
    Filozofia i Nauka; 2020, 8, 1; 31-67
    2300-4711
    2545-1936
    Pojawia się w:
    Filozofia i Nauka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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