What is it about?
A method inspired by the Singular Perturbation framework, able to extract the most meaningful part of a Markov chain for the long-run study of the associated modeled system.
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Why is it important?
The combinatorial explosion of the dimension of the Markov chain represents a critical bottleneck towards an efficient exploitation of this representation of a real system. A simple an effective reduction method is, therefore, essential, for the study of the most important characteristics of its behavior, on a long-run basis.
Perspectives
The meaning of slow and fast subsystems (characterizing the Singular Perturbation approaches) is interesting to further study and exploit, in the case of probabilistic models. These properties will be closer to an interpretation of strong and weak components ... To be followed ...
Professor Daniel Racoceanu
Pontifical Catholic University of Peru
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This page is a summary of: On a new method of Markov chain reduction, Mathematical Modelling of Systems, January 1995, Taylor & Francis,
DOI: 10.1080/13873959508837018.
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