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Reachability Analysis of Probabilistic Systems by Successive Refinements

机译:连续改进的概率系统的可达性分析

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摘要

We report on a novel development to model check quantitative reachability properties on Markov decision processes together with its prototype implementation. The innovation of the technique is that the analysis is performed on an abstraction of the model under analysis. Such an abstraction is significantly smaller than the original model and may safely refute or accept the required property. Otherwise, the abstraction is refined and the process repeated. As the numerical analysis necessary to determine the validity of the property is more costly than the refinement process, the technique profits from applying such numerical analysis on smaller state spaces.
机译:我们报告了一种新颖的开发,以模拟马尔可夫决策过程与原型实施。该技术的创新是,对正在分析的模型的抽象进行分析。这种抽象显着小于原始模型,并且可以安全地反驳或接受所需的财产。否则,提取抽象并重复过程。由于确定该性质的有效性所需的数值分析比细化过程更昂贵,因此在较小状态空间上对这种数值分析应用了这种数值分析的技术利润。

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