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The Hierarchy of System Specifications and the Problem of Structural Inference

Published online by Cambridge University Press:  28 February 2022

Bernard P. Zeigler
Bernard P. Zeigler*
Affiliation:
The Weizmann Institute of Science
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Extract

The activity of modelling proceeds by successive rounds of constructing abstract representations of reality and testing them against real world data. Since the testing is a comparison of behavior generated by the model with behavior observed for the modelled real system, it cannot directly validate the model structure, i.e., its claim as to how the real system works. This raises a central issue in modelling: is it possible to ascertain, even allowing an infinite comparison of behavioral data, that a model truly represents the mechanism underlying a real behavior?

To consider this issue, along with others of a similar fundamental nature, theories of modelling and simulation are being developed ([1], [2], 19]). The author's theory ([8], [9], [10]) consists of a set of postulates about the objects and activities involved in the modelling enterprise (a model of modelling) phrased within the theory of systems ([3], [5], [6], [7]) and employs the tools of the latter to consider such issues as the structural inference one mentioned above.

Type
Part VII. Mathematics and Philosophy of Science
Information
PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association , Volume 1976 , Issue 1: Volume One: Contributed Papers 1976 , 1976 , pp. 226 - 239
Copyright
Copyright © 1976 by the Philosophy of Science Association

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Footnotes

This work was partially supported by NSF Grant No. DCR71-01997, held by the Logic of Computers Group, University of Michigan, Ann Arbor, Michigan 48102, U.S.A.

References

Corynen, G.C. A Mathematical Theory of Modelling and Simulation. Unpublished Ph.D. Dissertation, University of Michigan, 1975. Xerox University Microfilms Publication Number 75-20319.Google Scholar
Jaron, J. “Functionisms and Morphisms of Complex Cybernetical Systems”, Cybernetica, 15 (1972): 26-38.Google Scholar
Klir, G.J. An Approach to General Systems Theory. New York: 1969, Von Nostrand Reinhold, 1969.Google Scholar
Kuhn, T. The Structure of Scientific Revolutions. Chicago: University of Chicago Press, 1962.Google Scholar
Mesaroic, M.D. and Takahara, Y. Foundations for a Mathematical System Theory. New York: Academic Press, 1974.Google Scholar
Padulo, L. and Arbib, M.A. Systems Theory. Philadelphia, Pa.: Saunders, 1974.Google Scholar
Wymore, A.W. A Mathematical Theory of Systems Engineering: The Elements. New York: Wiley and Sons, 1967.Google Scholar
Zeigler, B.P. “A Conceptual Basis for Modelling and Simulation”. Int. Jnl. Gen. Sys. 1 (1974): 213-228.CrossRefGoogle Scholar
Zeigler, B.P. Theory of Modelling and Simulation. New York: Wiley and Sons, 1976.Google Scholar
Zeigler, B.P. “Towards a Formal Theory of Modelling and Simulation: Structure Preserving Morphisms”. J.A.C.M. 19 (1972): 742- 764.Google Scholar
Zalecka-Melamed, A. The Inference of Network Structure for Discrete Time Systems. Unpublished Ph.D. Dissertation in progress at The University of Michigan.Google Scholar