Abstract
Often, we deal with black-box or grey-box systems where we can observe the overall system’s behavior, but we do not have access to the system’s internal structure. In many such situations, the system actually consists of two (or more) independent components: (a) how can we detect this based on observed system’s behavior? (b) what can we learn about the independent subsystems based on the observation of the system as a whole? In this paper, we provide (partial) answers to these questions.
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References
Th.H. Cormen, C.E. Leiserson, R.L. Rivest, C. Stein, Introduction to Algorithms (MIT Press, Cambridge, Massachusetts, 2009)
R. Feynman, R. Leighton, M. Sands, The Feynman Lectures on Physics (Addison Wesley, Boston, Massachusetts, 2005)
K.S. Thorne, R.D. Blandford, Modern Classical Physics: Optics, Fluids, Plasmas, Elasticity, Relativity, and Statistical Physics (Princeton University Press, Princeton, New Jersey, 2017)
Acknowledgements
This work was supported in part by the National Science Foundation grants 1623190 (A Model of Change for Preparing a New Generation for Professional Practice in Computer Science), and HRD-1834620 and HRD-2034030 (CAHSI Includes), and by the AT&T Fellowship in Information Technology.
It was also supported by the program of the development of the Scientific-Educational Mathematical Center of Volga Federal District No. 075-02-2020-1478, and by a grant from the Hungarian National Research, Development and Innovation Office (NRDI).
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Tizpaz-Niari, S., Kosheleva, O., Kreinovich, V. (2023). How to Detect (and Analyze) Independent Subsystems of a Black-Box (or Grey-Box) System. In: Ceberio, M., Kreinovich, V. (eds) Uncertainty, Constraints, and Decision Making. Studies in Systems, Decision and Control, vol 484. Springer, Cham. https://doi.org/10.1007/978-3-031-36394-8_40
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DOI: https://doi.org/10.1007/978-3-031-36394-8_40
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