We introduce two new measures of network robustness and apply them to four different strategies. The measures are independent from the number of nodes in the network and have the strong potential to cover a large portfolio of applications. Using the Monte-Carlo methods, we demonstrate how to...

For the multi-agent spatial Parrondo’s games, the available theoretical analysis methods based on the discrete-time Markov chain were assumed that the losing and winning states of an ensemble of N players were represented to be the system states. The number of system states was 2N types....

A new approach to determine the stability of multiple access network control schemes is presented. A “busy” network (the precise meaning of the term “busy” will be presented in the text) is modelled as a switched single-server hybrid dynamical system whose switching laws are stochastic...

We introduce the Conditional Mutual Information (CMI) for the estimation of the Markov chain order. For a Markov chain of K symbols, we define CMI of order m, Ic(m), as the mutual information of two variables in the chain being m time steps apart, conditioning on the intermediate variables of...

We extend the notion of Time Operator from Kolmogorov Dynamical Systems and Bernoulli processes to Markov processes. The general methodology is presented and illustrated in the simple case of binary processes. We present a method to compute the eigenfunctions of the Time Operator. Internal Ages...

This paper considers a memory-based persistent counting random walk, based on a Markov memory of the last event. This persistent model is a different than the Weiss persistent random walk model however, leading thereby to different results. We point out to some preliminary result, in particular,...

This paper proposes a Markov chain method to predict the growth dynamics of the individual nodes in scale-free networks, and uses this to calculate numerically the degree distribution. We first find that the degree evolution of a node in the BA model is a nonhomogeneous Markov chain. An...

A continuous state Markov chain of suitable order is employed to approximate the dynamics of surface wind speeds recorded at a single site. Using past observations, the model yields probabilistic forecasts of the future. We employ it for the prediction of turbulent gusts.

The congestion risk during escalator transfers was simulated based on a modified social force model. A four-stage transfer model was proposed. A projection strategy was employed to calculate the social forces for inclined surfaces, and a schedule-line model was proposed to calculate the targets...