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Efficient state space generation of GSPNs using decision diagrams

机译:使用决策图高效生成GSPN的状态空间

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Implicit techniques for representing and generating the reachability set of a high-level model have become quite efficient. However, such techniques are usually restricted to models whose events have equal priority. Models containing events with differing classes of priority or complex priority structure, in particular models with immediate events, have thus been required to use explicit reachability set generation techniques. In this paper, we present an efficient implicit technique, based on multi-valued decision diagram representations for sets of states and matrix diagram representations for next-state functions, that can handle models with complex priority structure. If the model contains immediate events, the vanishing states can be eliminated either during generation, by manipulating the matrix diagram, or after generation, by manipulating the multi-valued decision diagram. We apply both techniques to several models and give detailed results.
机译:用于表示和生成高级模型的可达性集的隐式技术已经变得非常有效。但是,此类技术通常仅限于事件具有相同优先级的模型。因此,需要包含具有不同优先级类别或复杂优先级结构的事件的模型,尤其是具有即时事件的模型,以使用显式的可达性集生成技术。在本文中,我们提出了一种有效的隐式技术,该技术基于状态集的多值决策图表示和下一状态函数的矩阵图表示,可以处理具有复杂优先级结构的模型。如果模型包含即时事件,则可以在生成过程中通过操作矩阵图或在生成之后通过操作多值决策图来消除消失状态。我们将两种技术都应用于几种模型并给出详细的结果。

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