@book{
 title = {Formalisms for specifying Markovian population models},
 type = {book},
 year = {2009},
 source = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
 volume = {5797 LNCS},
 id = {04c60d6e-f06d-3c26-b4b2-dd2bde45ce7f},
 created = {2017-12-21T13:50:26.573Z},
 file_attached = {false},
 profile_id = {bbb99b2d-2278-3254-820f-2de6d915ce63},
 last_modified = {2017-12-21T13:50:26.573Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {We compare several languages for specifying Markovian population models such as queuing networks and chemical reaction networks. These languages -matrix descriptions, stochastic Petri nets, stoichiometric equations, stochastic process algebras, and guarded command models- all describe continuous-time Markov chains, but they differ according to important properties, such as compositionality, expressiveness and succinctness, executability, ease of use, and the support they provide for checking the well-formedness of a model and for analyzing a model. © 2009 Springer Berlin Heidelberg.},
 bibtype = {book},
 author = {Henzinger, T.A. and Jobstmann, B. and Wolf, V.},
 doi = {10.1007/978-3-642-04420-5_2}
}

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