This paper presents the analysis of a renewal input  finite buffer queue wherein the customers can decide either to  join the queue with a probability or balk. The service process is Markovian service process ($MSP$) governed  by an underlying $m$-state Markov chain. Employing the supplementary  variable and imbedded Markov chain techniques,   the steady-state system length distributions at pre...

We compare two approaches for a Markovian model in flexible manufacturing systems (FMSs) using Monte Carlo simulation. The model, which is a development of Fazlollahtabar and Saidi-Mehrabad (2013), considers two features of automated flexible manufacturing systems equipped with automated guided vehicle (AGV), namely, the reliability of machines and the reliability of AGVs in a multiple AGV jobs...

in this paper, we investigate the delay-dependent robust stability of fuzzy cohen-grossberg neural networks with markovian jumping parameter and mixed time varying delays by delay decomposition method. a new lyapunov-krasovskii functional (lkf) is constructed by nonuniformly dividing discrete delay interval into multiple subinterval, and choosing proper functionals with different weighting matr...

The Reliability analysis of information and automation systems has to cope with complex system structures and a large number of different components. Adapted to these requirements, the Markovian minimal cut approach has been developed. The Markovian minimal cut approach combines the advantages of two well-known approaches, the minimal cut and the Markovian path approach. The minimal cut approac...

Models that combine Markovian states with implicit geometric state occupancy distributions and semi-Markovian states with explicit state occupancy distributions, are investigated. This type of model retains the flexibility of hidden semi-Markov chains for the modeling of short or medium size homogeneous zones along sequences but also enables the modeling of long zones with Markovian states. The...

OF DISSERTATION AN ECHO STATE MODEL OF NON-MARKOVIAN REINFORCEMENT LEARNING There exists a growing need for intelligent, autonomous control strategies that operate in real-world domains. Theoretically the state-action space must exhibit the Markov property in order for reinforcement learning to be applicable. Empirical evidence, however, suggests that reinforcement learning also applies to doma...

We propose using discrete dynamical systems to model non-Markovian processes. This implies a whole hierarchy of dynamical systems with dimensionality increasing proportional to the memory. Specific long-range memory effects are investigated for a quadratic, a cubic and a quartic map. Markovian processes transform the quadratic map into a normal form of the logistic equation; the H6non map corre...

A Markovian Petri net is a stochastic discrete event system frequently used for analysis and performance evaluation purposes. In the past, the fluidification has been proposed as a relaxation technique for avoiding the ”state explosion problem”. Following the same approach, in this paper a hybrid Petri net model is defined as a partial relaxation of an original Markovian Petri net. It is shown ...