Discrete Dynamics in Nature and Society
Volume 2 (1998), Issue 1, Pages 7-39

Dynamic system evolution and markov chain approximation

Roderick V. Nicholas Melnik

Mathematical Modelling & Numerical Analysis Group, Department of Mathematics and Computing, University of Southern Queensland, QLD 4350, Australia

Received 1 September 1997

Copyright © 1998 Roderick V. Nicholas Melnik. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In this paper computational aspects of the mathematical modelling of dynamic system evolution have been considered as a problem in information theory. The construction of mathematical models is treated as a decision making process with limited available information.The solution of the problem is associated with a computational model based on heuristics of a Markov Chain in a discrete space–time of events. A stable approximation of the chain has been derived and the limiting cases are discussed. An intrinsic interconnection of constructive, sequential, and evolutionary approaches in related optimization problems provides new challenges for future work.