Abstract
In the paper science is regarded as a self-adapting system consisting of two subsystems. The stochastic model of one of the subsystems is proposed. The model reflects changes of the structure of a scientific discipline. As an example a model for the physics of elementary particles is presented.
Similar content being viewed by others
References
In the paper the term “information” is used in the sense presented in: S. M. KOT, Information in economic systems,Folia Oeconomica Cracoviensia, Vol. XXVI, 1984, p. 115–126, (in polish).
see S. M. KOT, Mathematical models of information processes within the system of science,Zeszyty Naukowe Akademii Ekonomicznej w Krakowie, No. 64 (1984) 29.
H. REICHENBACH,The Rise of Scientific Philosophy, Berkeley, 1951.
T. S. KUHN,The Structure of Scientific Revolution, Univ. Chicago Press, London, 1970.
S. E. TULMIN,Human Understanding. The Collective Use and Evolution of Concepts, Princeton Univ. Press, Princeton, 1977.
K. R. POPPER, Logic of Scientific Discovery, London, 1956.
I. LAKATOS, Falsyfication and the methodology of scientific research programmes, in: I. LAKATOS, A. MUSGRAVE (Eds);Criticism and the Growth of Knowledge, Cambridge Univ. Press, Cambridge, 1970.
M. D. MESAROVIC, A. TAKAHARA,General Systems Theory: Mathematical Foundations, Academic Press, New York, 1975.
S. M. KOT, Information in economic systems,op. cit..
M. D. MESAROVIC, op. cit.
S. M. KOT: Applications of Markov chains to modelling and forecasting the information structure of a scientific branche,Int. Conf. on Costs and Benefits of Development of Science and Scientific Research, Cracow, Grand Valley, Sarajevo, June, 1981, Cracow Academy of Economics, Cracow, 1981.
see S. M. KOT, Mathematical models of information processe within the system of science, op. cit..
T. C. LEE, G. G. JUDGE, A. ZELLNER,Estimating the Parameters of the Markov Probability Model from Aggregate Time Series Data, North Holland Publ. Co., Amsterdam, 1970.
G. A. MILLER, Finite Markov processes in psychology,Psychometrica, No. 17 (1952) 149.
T. C. LEE, G. G. JUDGE, A. ZELLNER, op. cit. p. 35.
see J. G. KEMENY, J. L. SNELL,Finite Markov Chains, Princeton, 1960.
see W. GOFFMANN, G. HARMON, Mathematical approach to the prediction of scientific discoveryNature, 229 (1971) 103; M. NOWAKOWSKA,Theories of Research. Modelling Approaches, Warsaw, 1977, (in polish), p. 45–47.
see J. G. KEMENY, J. L. SNELL, op. cit.,Finite Markov Chains, Princeton, 1960. p. 78.
see the footnote 12..
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Kot, S.M. The stochastic model of evolution of scientific disciplines. Scientometrics 12, 197–205 (1987). https://doi.org/10.1007/BF02016292
Received:
Issue Date:
DOI: https://doi.org/10.1007/BF02016292