In this paper a Markov model for Evolutionary Multi-Agent System is recalled. The model allows to study dynamic features of the computation and increases understanding the considered classes of systems by e.g., proving the ergodicity of the Markov chain modelling EMAS. This feature may be considered as a reason to use such complex techniques, as following the Michael Vose's approach, similar feature is proven for EMAS, showing that this system is able to reach any possible state of the system space (including of course optima sought). The main contribution of the paper is showing possibilities of applying the already proposed model to dynamic optimization problems. The impact of these enhancements on the ergodicity feature is also discussed.
