Adaptive Aggregation of Markov Chains: Quantitative Analysis of Chemical Reaction Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F15%3A00081179" target="_blank" >RIV/00216224:14330/15:00081179 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-21690-4_12" target="_blank" >http://dx.doi.org/10.1007/978-3-319-21690-4_12</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-21690-4_12" target="_blank" >10.1007/978-3-319-21690-4_12</a>
Alternative languages
Result language
angličtina
Original language name
Adaptive Aggregation of Markov Chains: Quantitative Analysis of Chemical Reaction Networks
Original language description
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 scalability of the numerical schemes. However, none of the existing numerical techniques provides general, explicit bounds on the approximation error, a problem particularly relevant when the level of accuracy affects the soundness of verification results. We propose a novel numerical approach that combines the strengths of aggregation techniques (state-space reduction) with those of simulation-based approaches (automatic updates that adapt to the process dynamics). The key advantage of our scheme is that it provides rigorous precision guarantees under different measures.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
—
Result continuities
Project
<a href="/en/project/GA15-11089S" target="_blank" >GA15-11089S: Parameter Discovery for Biological Models Using Model Checking</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
27th International Conference, CAV 2015, San Francisco, CA, USA, July 18-24, 2015, Proceedings
ISBN
9783319216898
ISSN
0302-9743
e-ISSN
—
Number of pages
19
Pages from-to
195-213
Publisher name
Springer International Publishing
Place of publication
Berlin
Event location
San Francisco
Event date
Jan 1, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—