Dynamic system evolution and Markov chain approximation
type: Item
instance of: scholarly article
title: Dynamic system evolution and Markov chain approximation
zbMATH Open document ID: 0933.93064
DOI: 10.1155/S1026022698000028
author: R. V. N. Melnik
published in: Discrete Dynamics in Nature and Society
publication date: 2000-04-04T00:00:00Z
full work available at URL: https://eudml.org/doc/120178
review text: Mathematical modelling of dynamic system evolution is studied here as a problem in information theory. The construction of mathematical models is treated as a decision making process with limited information, and computational models for evolution are derived using the Markov chain approximations. Particularly, a stable approximation for the hyperbolic model is obtained and an algorithm is given. Some closely related results of the author on the associated stochastic optimal control are published somewhere else [cf. IEEE Int. Symp. Information Theory, Ulm; Germany, June 29--July 4 (1997), IEEE Catalog No. 97CH36074; Numer. Funct. Anal. Optimization 18, No. 3-4, 401-426 (1997; Zbl 0879.49006)].
reviewed by: Chengxun Wu
Mathematics Subject Classification ID: 93E03
Mathematics Subject Classification ID: 93A30
Mathematics Subject Classification ID: 93E20
zbMATH DE Number: 1337770
zbMATH Keywords: hyperbolicity of dynamic rules
zbMATH Keywords: mathematical modelling
zbMATH Keywords: information theory
zbMATH Keywords: decision making
zbMATH Keywords: stochastic optimal control
MaRDI profile type: Publication
OpenAlex ID: W1972788618
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description: scientific article; zbMATH DE number 1337770