Formalisms for specifying Markovian population models
T.A. Henzinger, B. Jobstmann, V. Wolf, IJFCS: International Journal of Foundations of Computer Science 22 (2011) 823–841.
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Abstract
In this survey, we compare several languages for specifying Markovian population models such as queuing networks and chemical reaction networks. All these languages — matrix descriptions, stochastic Petri nets, stoichiometric equations, stochastic process algebras, and guarded command models — describe continuous-time Markov chains, but they differ according to important properties, such as compositionality, expressiveness and succinctness, executability, and ease of use. Moreover, they provide different support for checking the well-formedness of a model and for analyzing a model.
Publishing Year
Date Published
2011-06-01
Journal Title
IJFCS: International Journal of Foundations of Computer Science
Volume
22
Issue
4
Page
823 - 841
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Henzinger TA, Jobstmann B, Wolf V. Formalisms for specifying Markovian population models. IJFCS: International Journal of Foundations of Computer Science. 2011;22(4):823-841. doi:10.1142/S0129054111008441
Henzinger, T. A., Jobstmann, B., & Wolf, V. (2011). Formalisms for specifying Markovian population models. IJFCS: International Journal of Foundations of Computer Science, 22(4), 823–841. https://doi.org/10.1142/S0129054111008441
Henzinger, Thomas A, Barbara Jobstmann, and Verena Wolf. “Formalisms for Specifying Markovian Population Models.” IJFCS: International Journal of Foundations of Computer Science 22, no. 4 (2011): 823–41. https://doi.org/10.1142/S0129054111008441.
T. A. Henzinger, B. Jobstmann, and V. Wolf, “Formalisms for specifying Markovian population models,” IJFCS: International Journal of Foundations of Computer Science, vol. 22, no. 4, pp. 823–841, 2011.
Henzinger TA, Jobstmann B, Wolf V. 2011. Formalisms for specifying Markovian population models. IJFCS: International Journal of Foundations of Computer Science. 22(4), 823–841.
Henzinger, Thomas A., et al. “Formalisms for Specifying Markovian Population Models.” IJFCS: International Journal of Foundations of Computer Science, vol. 22, no. 4, World Scientific Publishing, 2011, pp. 823–41, doi:10.1142/S0129054111008441.
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