Computing cumulative rewards using fast adaptive uniformisation

Frits Dannenberg, Ernst Moritz Hahn, Marta Kwiatkowska

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

5 Citations (Scopus)


The computation of transient probabilities for continuoustime Markov chains often employs uniformisation, also known as the Jensen's method. The fast adaptive uniformisation method introduced by Mateescu approximates the probability by neglecting insignificant states, and has proven to be effective for quantitative 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.

Original languageEnglish
Title of host publicationComputational Methods in Systems Biology - 11th International Conference, CMSB 2013, Proceedings
Number of pages17
Publication statusPublished - 2013
Externally publishedYes
Event11th International Conference on Computational Methods in Systems Biology, CMSB 2013 - Klosterneuburg, Austria
Duration: 22 Sept 201324 Sept 2013
Conference number: 11

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8130 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th International Conference on Computational Methods in Systems Biology, CMSB 2013
Abbreviated titleCMSB 2013


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