2004
Volume 113, Issue 1
  • ISSN: 0002-5275
  • E-ISSN: 2352-1244

Abstract

Abstract

Recent successes within Artificial Intelligence with deep learning techniques in board games gave rise to the ambition to apply these learning methods to scientific discovery. This model for discovering new scientific laws is based on data-driven generalization in large databases with observational data using neural networks. In this study we want to review and critical assess an earlier research programme by the name of BACON. Though BACON was based on different AI technology, we can learn from its limitations and thus adjust our expectations. The BACON program had two ambitions, one descriptive and one normative. On the one hand, it wanted to provide an explanation how philosophers of nature in history arrived at general laws from observational data and on the other hand it also aimed to reconstruct historical discoveries and realize new ones. We will assess the claims of the BACON program by means of two historical cases studies: the discovery of the sine law of refraction in optics and the discovery of Kepler’s third law of planetary motion. I will demonstrate that, despite the formulated claims, BACON did not use the same historical data available to its discoverers and, more importantly, that the model of inductive generalization of observational data does not correspond with the historical methods. Finally I will question the value of data-driven induction for scientific discovery in general.

Loading

Article metrics loading...

/content/journals/10.5117/ANTW2021.1.003.HEEF
2021-02-01
2021-11-29
Loading full text...

Full text loading...

/deliver/fulltext/00025275/113/1/04_ANTW2021.1_HEEF.html?itemId=/content/journals/10.5117/ANTW2021.1.003.HEEF&mimeType=html&fmt=ahah

References

  1. Adam, C., & Tannery, P. (Eds.). (1896-1909). Oeuvres de Descartes (vol. 11). Paris: Librairie Philosophique J. Vrin.
  2. Corley, C. e.a.(2018)Deep Learning for Scientific Discovery. The Next Wave, 22 (1), 27-31.
    [Google Scholar]
  3. Donahue, W.(2000). Kepler’s optics. Green Lion, Santa Fe.
  4. Downes, S.(1990). Herbert Simon's Computational Models of Scientific Discovery, PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association, Volume One: Contributed Papers, pp. 97-108
    [Google Scholar]
  5. Gingerich, O.(1975). The origins of Kepler’s third law. In: A.Beer & P.Beer (Eds.), Kepler: Four hundred years (Vistas in astronomy, vol. 18, pp. 595-601). New York: Pergamon.
    [Google Scholar]
  6. Goddu, A.(2010). Copernicus and the Aristotelian tradition: education, reading and philosophy in Copernicus’s path to heliocentrism. Leiden: Brill.
  7. Govi, G.(1885). L’Ottica die Cl. Tolomeo da Eugenio. Torino.
  8. Groot, Adriaan de.1946. Het denken van den schaker. Doctoraal proefschrift, Noord-Hollandse uitgeverij maatschappij, Amsterdam.
  9. Groot, Adriaan de.1965. Thought and choice in chess. Den Haag: Mouton.
  10. Heeffer, A.(2003). Kepler’s near discovery of the sine law: A qualitative computational model. In: C.Delrieux & J.Legris (Eds.), Computer modeling of scientific reasoning (pp. 93-102). Bahia Blanca: Universidad Nacional del Sur.
    [Google Scholar]
  11. Heeffer, A.(2006). The logic of disguise: Descartes’ discovery of the sine law. Historia scientiarum. International Journal of the History of Science Society of Japan, 16 (2), 144-165.
    [Google Scholar]
  12. Heeffer, A.(2017)“Looking for invariances in geometrical diagrams: Della Porta, Kepler and Descartes on refraction,” in Zik, Pastorino, Hon and Borrelli (eds.) The Optics of Della Porta: a reassessment,Archimedes Series, Springer, New York, 145-168.
    [Google Scholar]
  13. Hempel, C.(1945). Studies in the logic of confirmation. Mind, 54(1-26), 97-121.
    [Google Scholar]
  14. Kepler, J.(1596). Prodromus dissertationum cosmographicarum, continens mysterium cosmographicum, de admirabili proportione orbium coelestium …: Demonstratum, per quinque regularia corpora geometrica, Gruppenbach, Tübingen. [A. M. Duncan, Trans. with notes by Aiton, E. J. (1986) The Secret of the Universe. New York, Abaris. Books.]
  15. Kepler, J.(1604). Ad Vitellionem paralipomena, quibus astronomiae pars optica traditor … Claudius Marnius & heirs of Johann Aubrius: Frankfurt. See Donahue (2000). Kepler’s Optics. Santa Fe: Green Lion.
  16. Kepler, J.(1619). Harmonices Mundi Libri V (Translated into English with an Introduction and Notes by Aiton, E. J., Duncan, A. M., & Field, J. V., 1997). Linz: Ioannes Plancus.
  17. Kepler, J. (1858-1871). Joannis Kelpleri Astronomi Opera Omnia. Frankfurt: Heyder and Zimmer.
  18. Koestler, A.(1959). The sleepwalkers: A history of man’s changing vision of the universe. London: Hutchinson.
  19. Kramer, P. M.(1882). Descartes und das Brechungsgesetz des Lichtes. Abhandlungen zur Geschichte der Mathematik. Zeitschrift für Mathematik und Physik, XXVII, 233-278.
    [Google Scholar]
  20. Langley, P., Bradshaw, G. L., & Simon, H. A.(1981). BACON.5: The discovery of conservation laws. Proceedings of the Seventh International Joint Conference on Artificial Intelligence, 1, 121-126.
    [Google Scholar]
  21. Langley, P., Simon, H. A., Bradshaw, G. L., & Zytow, J. M.(1987). Scientific discovery: Computational explorations of the creative processes. Cambridge, MA: MIT.
  22. Lejeune, A.(1956). Ptolémée. L’optique de Claude Ptolémée dans la version latine d’après l’arabe de l’émir Eugène de Sicile. Edition critique et exégétique par Albert Lejeune. Publications universitaires de Louvain.
  23. Litjens, Geert e.a.2017. A survey on deep learning in medical image analysis, Medical Image Analysis, 42, December 2017, pp. 60-88, doi:https://doi.org/10.1016/j.media.2017.07.005.
    [Google Scholar]
  24. Michie, D., and A.Srinivasan. 2009. Donald Michie on machine intelligence, biology and more. Oxford: Oxford University Press.
  25. Neugebauer, O.(1957). The exact sciences in antiquity (2nd ed.). Reprinted by Dover 1969. Princeton: Princeton University Press.
  26. Newell, A., Simon, H.(1972). Human problem solving. Englewood Cliffs: Prentice-Hall.
  27. Nickles, T.(1994). Enlightenment versus romantic models of creativity in science – and beyond. Creativity Research Journal, 7, 277-314.
    [Google Scholar]
  28. Popova, M, Isayev, O., Tropsha, A.2018. Deep reinforcement learning for de novo drug design, Science Advances, 25 Jul 2018: Vol. 4, no. 7DOI:10.1126/sciadv.aap7885.
    [Google Scholar]
  29. Popper, K. R.(1959). The logic of scientific discovery. New York: Basic Book.
  30. Reichenbach, H.(1938). Experience and prediction. Chicago: University of Chicago Press.
  31. Risner, F. (Ed.) (1572). Opticae Thesaurus. Basel: Per Episcopios.
  32. Rumelhart DavidE., James L.McClelland and PDP Research Group(1987). Parallel Distributed Processing: Explorations in the Microstructure of Cognition, MIT Press, Boston, Ma.
  33. Schuster, J. A.(1978). Descartes and the scientific revolution, 1618-1634: An interpretation. PhD thesis, Princeton University, University Microfilms International, Ann Arbor.
  34. Shea, W. R.(1991). The magic of numbers and motion: The scientific career of René Descartes. Cambridge: Science History Publications.
  35. Silver, David e.a.2018. A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play. Science 07 Dec 2018:, Vol. 362, Issue 6419, pp. 1140-1144, DOI:10.1126/science.aar6404
    [Google Scholar]
  36. Smith, A. M.(1996). Ptolemy’s theory of visual perception: An English translation of the optics with introduction and commentary. Philadelphia: American Philosophical Society.
  37. Stephenson, B.(1994). The music of the heavens: Kepler’s harmonic astronomy. Princeton: Princeton University Press.
  38. Unguru, S. (Ed.). (1977). Witelonis perspectiva, liber primus. An English translation with introduction and commentary and Latin edition of the mathematical book of Witelo’s Perspectiva, Studia Copernicana, XV. Warsaw: Polish Academy of Sciences.
  39. Volgraff, J. A.(1918). Risneri Opticum cum Annotationibus Willebrordi Snellii. Gent: Aedibus Plantini.
http://instance.metastore.ingenta.com/content/journals/10.5117/ANTW2021.1.003.HEEF
Loading
/content/journals/10.5117/ANTW2021.1.003.HEEF
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): artificial intelligence; Herbert Simon; induction; scientific discovery; sine law
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error