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  1. Transactions on Modeling and Computer Simulation (TOMACS)
  2. ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 25
  3. Issue 2(Special Issue on Computational Methods in Systems Biology), April 2015
  4. Computing Cumulative Rewards Using Fast Adaptive Uniformization
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ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 27
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 26
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 25
Issue 4(Special Issue on Don Iglehart), November 2015
Issue 3, May 2015
Issue 2(Special Issue on Computational Methods in Systems Biology), April 2015
Guest Editors’ Introduction to Special Issue on Computational Methods in Systems Biology
Moment-Based Methods for Parameter Inference and Experiment Design for Stochastic Biochemical Reaction Networks
Computing Cumulative Rewards Using Fast Adaptive Uniformization
Simulating Organogenesis: Algorithms for the Image-Based Determination of Displacement Fields
Constrained Community-Based Gene Regulatory Network Inference
Model Reconstruction for Moment-Based Stochastic Chemical Kinetics
Spatial-Temporal Modelling and Analysis of Bacterial Colonies with Phase Variable Genes
Hybrid Simulations of Heterogeneous Biochemical Models in SBML
Issue 1, January 2015
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 24
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 23
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 22
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 21
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 20
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 19
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 18
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 17
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 16
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 15
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 14
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 13
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 12
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 11
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 10
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 9
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 8
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 7
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 6
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 5
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 4
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 3
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 2
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 1

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Article

Computing Cumulative Rewards Using Fast Adaptive Uniformization

Content Provider ACM Digital Library
Author Kwiatkowska, Marta Hahn, Ernst Moritz Dannenberg, Frits
Copyright Year 2015
Abstract The computation of transient probabilities for continuous-time Markov chains often employs uniformization, also known as the Jensen method. The fast adaptive uniformization method introduced by Mateescu et al. 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 $\textit{t}.$ In this article, we extend fast adaptive uniformization to handle expected reward properties that reason about the model behavior until time $\textit{t},$ for example, the expected number of chemical reactions that have occurred until $\textit{t}.$ 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. The performance of the method is enhanced by the use of interval splitting. We compare our implementation to standard uniformization implemented in PRISM and to fast adaptive uniformization without support for cumulative rewards implemented in MARCIE, demonstrating superior performance.
Starting Page 1
Ending Page 23
Page Count 23
File Format PDF
ISSN 10493301
e-ISSN 15581195
DOI 10.1145/2688907
Volume Number 25
Issue Number 2
Journal ACM Transactions on Modeling and Computer Simulation (TOMACS)
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2015-02-17
Publisher Place New York
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword DNA computation DNA strand displacement Markov models Probabilistic model checking Fast adaptive uniformisation Quantitative model checking
Content Type Text
Resource Type Article
Subject Computer Science Applications Modeling and Simulation
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