This paper reports simulation experiments, applying the cross entropy method such as the importance sampling algorithm for efficient estimation of rare event probabilities in Markovian reliability systems. The method is compared to various failure biasing schemes that have been proved to give estimators with bounded relative errors. The results from the experiments indicate a considerable improvement of the performance of the importance sampling estimators, where performance is mea-sured by the relative error of the estimate, by the relative error of the estimator,and by the gain of the importance sampling simulation to the normal simulation. Keywords: reliability, Markov chains, rare event simulation, importance sampling, cross entropy File-Url: https://papers.tinbergen.nl/04018.pdf File-Format: application/pdf File-Size: 221197 bytes Handle: RePEc:tin:wpaper:20040018