Algorithmic minimization of uncertain continuous-time Markov chains
The assumption of perfect knowledge of rate parameters in continuous-time Markov chains (CTMCs) is undermined when confronted with reality, where they may be uncertain due to lack of information or because of measurement noise. Here we consider uncertain CTMCs (UCTMCs), where rates are assumed to va...
Auteurs principaux: | Cardelli, L, Grosu, R, Larsen, KG, Tribastone, M, Tschaikowski, M, Vandin, A |
---|---|
Format: | Journal article |
Langue: | English |
Publié: |
IEEE
2023
|
Documents similaires
-
Lumpability for uncertain continuous-time Markov chains
par: Cardelli, L, et autres
Publié: (2021) -
Comparing chemical reaction networks: a categorical and algorithmic perspective
par: Cardelli, L, et autres
Publié: (2016) -
Comparing chemical reaction networks: A categorical and algorithmic perspective
par: Cardelli, L, et autres
Publié: (2017) -
Syntactic markovian bisimulation for chemical reaction networks
par: Cardelli, L, et autres
Publié: (2017) -
Guaranteed Error Bounds on Approximate Model Abstractions through Reachability Analysis
par: Cardelli, L, et autres
Publié: (2018)