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  • 标题:Statistical Verification of PCTL Using Stratified Samples
  • 本地全文:下载
  • 作者:Yu Wang ; Nima Roohi ; Matthew West
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2018
  • 卷号:51
  • 期号:16
  • 页码:85-90
  • DOI:10.1016/j.ifacol.2018.08.015
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this work, we propose a stratified sampling method to statistically check Probabilistic Computation Tree Logic (PCTL) formulas on discrete-time Markov chains with sequential probability ratio test. Distinct from previous statistical verification methods using independent Monte Carlo sampling, our algorithm uses stratified samples that are negatively correlated, thus give lower variance. The experiments demonstrate that the new algorithm uses a smaller number of samples for a given confidence level on several benchmark examples.
  • 关键词:KeywordsMarkov chainsTemporal logicVariance reductionPRISMSequential probability ratio test
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