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Approximate symbolic model checking of continuous-time markov chains (extended )abstract

机译:连续时间马尔可夫链(延长)摘要近似符号模型检查

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This paper presents a symbolic model checking algorithm for continuous-time Markov chains for an extension of the continuous stochastic logic CSL of Aziz et al [1]. The considered logic contains a time-bounded until-operator and a novel operator to express steady-state probabilities. We show that the model checking problem for this logic reduces to a system of linear equations (for unbounded until and the steady state-operator) and a Volterra integral equation system for time-bounded until. We propse a symbolic approximate method for solving the integrals using MTDDs (multi-terminal decision diagrams), a generalisation of MTBDDs. These new structures are suitable for numerical integration using quadrature formulas based on equally-spaced abscissas, like trapezoidal, Simpson and Romberg integration schemes.
机译:本文介绍了连续时间马尔可夫链的符号模型检查算法,用于Aziz等[1]的连续随机逻辑CSL的扩展。所考虑的逻辑包含一个时间有限于 - 运营商和一个新的操作员,以表达稳态概率。我们表明,该逻辑的模型检查问题减少到线性方程系统(用于无限的直到和稳态运算符),以及用于时间限定的Volterra积分方程系统直到。我们提出了一种符号近似方法,用于使用MTDDS(多终端判定图),MTBDD的泛化来解决积分。这些新结构适用于使用基于同等间隔的横坐标的正交公式的数值积分,如梯形,辛普森和罗姆伯格集成方案。

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