Abstract
Multidimensional Markov chains can be used to model systems that are formed of interacting subsystems. This can be achieved by associating a submodel with each subsystem, identifying the state space of each submodel, and characterizing the transitions in which each submodel participates. The states such a model occupies are often a proper subset of the Cartesian product of its submodel state spaces.
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Dayar, T. (2018). Conclusion. In: Kronecker Modeling and Analysis of Multidimensional Markovian Systems. Springer Series in Operations Research and Financial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-97129-2_8
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DOI: https://doi.org/10.1007/978-3-319-97129-2_8
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