Analyzing Non-Markovian Systems by Using a Stochastic Process Calculus and a Probabilistic Model Checker

Analyzing Non-Markovian Systems by Using a Stochastic Process Calculus and a Probabilistic Model Checker

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The non-Markovian Mug systems represent almost all stochastic processes, except of a small class having the Markov property; it is a real challenge to analyze these systems.In this article, we present a general method of analyzing non-Markovian systems.The novel viewpoint is given by the use of a compact stochastic process calculus developed in the formal framework of computer science for describing concurrent systems.Since phase-type distributions can approximate non-Markovian systems with arbitrary precision, we approximate a non-Markovian system by describing it easily in our stochastic process calculus, which employs phase-type distributions.The obtained process (in our calculus) are then translated into the probabilistic model checker PRISM; by using this free software tool, we can analyze several quantitative properties of the Markovian approximation of the initial bellfordtoysandhobbiers.shop non-Markovian system.