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Computing cumulative rewards using fast adaptive uniformisation (2013)
| Venue: | In CMSB, volume 8130 of LNCS |
| Citations: | 5 - 5 self |
BibTeX
@INPROCEEDINGS{Dannenberg13computingcumulative,
author = {Frits Dannenberg and Ernst Moritz Hahn and Marta Kwiatkowska},
title = {Computing cumulative rewards using fast adaptive uniformisation},
booktitle = {In CMSB, volume 8130 of LNCS},
year = {2013},
pages = {33--49},
publisher = {Springer}
}
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Abstract
Abstract.The computation of transient probabilities for continuous-time Markov chains often employs uniformisation, also known as the Jensen’s method. The fast adaptive uniformisation method introduced by Mateescu approximates the proba-bility by neglecting insignificant states, and has proven to be effective for quanti-tative analysis of stochastic models arising in chemical and biological applications. However, this method has only been formulated for the analysis of properties at a given point of time t. In this paper, we extend fast adaptive uniformisation to handle expected reward properties which reason about the model behaviour until time t, for example, the expected number of chemical reactions that have occurred until t. To show the feasibility of the approach, we integrate the method into the probabilistic model checker PRISM and apply it to a range of biological models, demonstrating superior performance compared to existing techniques. 1
Keyphrases
adaptive uniformisation cumulative reward quanti-tative analysis jensen method insignificant state reward property stochastic model model behaviour transient probability superior performance continuous-time markov chain chemical reaction biological model expected number probabilistic model checker prism fast adaptive uniformisation method biological application
