DEVS markov modeling and simulation: formal definition and implementation

Markov Modeling is among the most commonly used forms of model expression and Markov concepts of states and state transitions are fully compatible with the DEVS characterization of discrete event systems. Besides their general usefulness, the Markov concepts of stochastic modeling are implicitly at the heart of most forms of discrete event simulation and are a natural basis for the extended and integrated Markov modeling facility discussed in this paper. DEVS Markov models are full-fledged DEVS models and can be coupled with other DEVS components in hierarchical compositions. Due to their explicit transition and time advance structure, DEVS Markov models can be individualized with specific transition probabilities and transition times/rates which can be changed during model execution for dynamic structural change. This paper presents the formal concepts underlying DEVS Markov models and how they are implemented in MS4 Me, also discussing how the facilities differ from other Markov M&S tools.