The usual methods of applying Bayesian networks to the modeling of temporal processes, such as Dean and Kanazawa's dynamic Bayesian networks (DBNs), consist in discretizing t...
This paper addresses several issues of using the mathematical programming representations of discrete-event dynamic systems in perturbation analysis. In particular, linear program...
Advances in massively parallel platforms are increasing the prospects for high performance discrete event simulation. Still the di culty in parallel programming persists and there...
Stochastic Flow Models (SFMs) are stochastic ystems that abstract the dynamics of complex discrete event systems involving the control of sharable resources. SFMs have been used to...
In this paper, two anticontrol algorithms for synthesis of discrete chaos are introduced. In these algorithms, the control parameter of a discrete dynamical system is switched, ei...