Computing as Empirical Science – Evolution of a Concept

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Abstract

This article presents the evolution of philosophical and methodological considerations concerning empiricism in computer/computing science. In this study, we trace the most important current events in the history of reflection on computing. The forerunners of Artificial Intelligence H.A. Simon and A. Newell in their paper Computer Science As Empirical Inquiry (1975) started these considerations. Later the concept of empirical computer science was developed by S.S. Shapiro, P. Wegner, A.H. Eden and P.J. Denning. They showed various empirical aspects of computing. This led to a view of the science of computing (or science of information processing) - the science of general scope. Some interesting contemporary ways towards a generalized perspective on computations were also shown (e.g. natural computing).

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  • Abramsky S. 2008. Information Processes and Games in: Adriaans P. Benthem J. van (Eds.) Philosophy of Information. North Holland Amsterdam The Netherlands; Boston pp. 483-549.

  • Brent R. Bruck J. 2006. 2020 Computing: Can computers help to explain biology? Nature 440 416-417. doi:

    • Crossref
    • Export Citation
  • Burgin M. Dodig-Crnkovic G. 2013. Typologies of Computation and Computational Models. arXiv:1312.2447 [cs].

  • Colburn T.R. Fetzer J.H. Terry L Rankin (Eds.) 1993. Program verification: fundamental issues in computer science. Kluwer Academic Publishers Dordrecht; Boston.

  • Denning P.J. 2009. Beyond Computational Thinking. Communications of the ACM 52 28-30. doi:

    • Crossref
    • Export Citation
  • Denning P.J. 2007. Computing is a Natural Science. Communications of the ACM 50 13-18. doi:

    • Crossref
    • Export Citation
  • Denning P.J. 2005. Is Computer Science Science? Communications of the ACM 48 27-31. doi:

    • Crossref
    • Export Citation
  • Dodig-Crnkovic G. 2012. Alan Turing’s Legacy: Info-Computational Philosophy of Nature. arXiv:1207.1033 [cs].

  • Dodig-Crnkovic G. 2004. Scientific Methods in Computer Science [WWW Document]. Proceedings of the Conference for the Promotion of research in IT at New Universities and University Colleges in Sweden. URL http://www.mrtc.mdh.se/publications/0446.pdf (accessed 10.21.14).

  • Dodig-Crnkovic G. Giovagnoli R. 2013. Computing nature: Turing centenary perspective. Springer Heidelberg New York.

  • Dodig-Crnkovic G. Giovagnoli R. 2012. Computing Nature: A Network of Networks of Concurrent Information Processes. arXiv:1210.7784 [cs].

  • Eden A.H. 2007. Three Paradigms of Computer Science. Minds and Machines 17 135-167. doi:

    • Crossref
    • Export Citation
  • Fetzer J.H. 1988. Program Verification: The Very Idea. Communications of the ACM 31 1048-1063. doi:

    • Crossref
    • Export Citation
  • Flasiński M. 2011. Wstęp do sztucznej inteligencji (Introduction to Artificial Intelligence). Wydawnictwo Naukowe PWN Warszawa.

  • Harel D. 1987. Algorithmics: the spirit of computing. Addison-Wesley Wokingham England; Reading Mass.

  • Hayek F.A. v. 1940. Socialist Calculation: The Competitive ‘Solution’. Economica New Series 7 125-149. doi:

    • Crossref
    • Export Citation
  • Knuth D.E. 1974. Computer science and its relation to mathematics. The American Mathematical Monthly 81 323-343.

  • Leciejewski S. 2013. Cyfrowa rewolucja w badaniach eksperymentalnych: studium metodologiczno-filozoficzne (The digital revolution in experimental research: methodological and philosophical study) Seria Filozofia i Logika. Wydawnictwo Naukowe Uniwersytetu im. Adama Mickiewicza Poznań.

  • Marciszewski W. 2005. Wolny rynek jako system przetwarzania informacji (Free Market as Information-Processing System) in: Heller M. Mączka J. (Eds.) Informacja a rozumienie. Wydawnictwo Diecezji Tarnowskiej Biblos; Polska Akademia Umiejętności. Ośrodek Badań Interdyscyplinarnych Tarnow; Krakow pp. 235-267.

  • Mises L. von 2012. Economic calculation in the socialist commonwealth. Ludwig Von Mises Institute Auburn University Auburn Alabama.

  • Mises L. von 1920. Die Wirtschaftsrechnung im sozialistischen Gemeinwesen. Archiv für Sozialwissenschaft und Sozialpolitik 47 86-121.

  • Newell A. Simon H.A. 1976. Computer Science As Empirical Inquiry: Symbols and Search. Communications of the ACM 19 113-126. doi:

    • Crossref
    • Export Citation
  • Noah Smith David Smith 2005. Empirical Research Methods in Computer Science [WWW Document]. URL http://www.cs.jhu.edu/~nasmith/erm/ (accessed 10.22.14).

  • Rapaport W. 2005. Philosophy of Computer Science: An Introductory Course. Teaching Philosophy 28 319-341.

  • Sarosiek A. 2013. Proby aplikacji paradygmatu ucieleśnionego umysłu w tworzeniu sztucznej inteligencji (An attempt of application of the embodied mind paradigm to the development of artificial intelligence). Semina Scientiarum 12 97-107.

  • Shapiro S.S. 2001. Computer Science: The Study of Procedures [WWW Document]. URL http://www.cse.buffalo.edu/~shapiro/Papers/whatiscs.pdf (accessed 10.21.14).

  • Stacewicz P. Marciszewski W. 2011. Umysł - komputer - świat. O zagadce umysłu z informatycznego punktu widzenia (Mind - computer - world: On the Riddle of Mind from an Informational Point of View). Akademicka Oficyna Wydawnicza EXIT.

  • Tedre M. 2011. Computing As a Science: A Survey of Competing Viewpoints. Minds and Machines 21 361-387. doi:

    • Crossref
    • Export Citation
  • Tedre M. 2006. The Development of Computer Science: A Sociocultural Perspective University of Joensuu Computer Science Dissertations. University of Joensuu Department of Computer Science and Statistics Joensuu.

  • Wegner P. 1976. Research Paradigms in Computer Science in: Proceedings of the 2nd International Conference on Software Engineering ICSE ’76. IEEE Computer Society Press Los Alamitos CA USA pp. 322-330.

  • Winsberg E.B. 2014. Computer Simulations in Science [WWW Document]. The Stanford Encyclopedia of Philosophy. URL http://plato.stanford.edu/archives/fall2014/entries/simulations-science/ (accessed 10.21.14).

  • Winsberg E.B. 2010. Science in the age of computer simulation. University of Chicago Press Chicago.

  • Zenil H. (Ed.) 2013. A computable universe: understanding and exploring nature as computation. World Scientific Singapore.

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