Adaptive Aggregation of Markov Chains: Quantitative Analysis of Chemical Reaction Networks
Quantitative analysis of Markov models typically proceeds through numerical methods or simulation-based evaluation. Since the state space of the models can often be large, exact or approximate state aggregation methods (such as lumping or bisimulation reduction) have been proposed to improve the sca...
Auteurs principaux: | Abate, A, Brim, L, Ceska, M, Kwiatkowska, M |
---|---|
Format: | Conference item |
Langue: | English |
Publié: |
2015
|
Documents similaires
-
Approximate policy iteration for Markov decision processes via quantitative adaptive aggregations
par: Abate, A, et autres
Publié: (2016) -
Adaptive formal approximations of Markov chains
par: Abate, A, et autres
Publié: (2021) -
Designing robust software systems through parametric markov chain synthesis
par: Kwiatkowska, M, et autres
Publié: (2017) -
Syntax-guided optimal synthesis for chemical reaction networks
par: Cardelli, L, et autres
Publié: (2017) -
Exploring Parameter Space of Stochastic Biochemical Systems Using Quantitative Model Checking
par: Brim, L, et autres
Publié: (2013)