Difference between revisions of "Publications/herault.06.qest"
From LRDE
(Created page with "{{Publication | date = 2006-01-01 | authors = Thomas Hérault, Richard Lassaigne, Sylvain Peyronnet | title = APMC 3.0: Approximate verification of Discrete and Continuous Tim...") |
|||
| Line 8: | Line 8: | ||
| urllrde = 200606-Qest |
| urllrde = 200606-Qest |
||
| abstract = In this paper, we give a brief overview of APMC (Approximate Probabilistic Model Checker). APMC is a model checker that implements approximate probabilistic verification of probabilistic systems. It is based on Monte-Carlo method and the theory of randomized approximation schemes and allows to verify extremely large models without explicitly representing the global transition system. To avoid the state-space explosion phenomenon, APMC gives an accurate approximation of the satisfaction probability of the property instead of the exact value, but using only a very small amount of memory. The version of APMC we present in this paper can now handle efficiently both discrete and continuous time probabilistic systems. |
| abstract = In this paper, we give a brief overview of APMC (Approximate Probabilistic Model Checker). APMC is a model checker that implements approximate probabilistic verification of probabilistic systems. It is based on Monte-Carlo method and the theory of randomized approximation schemes and allows to verify extremely large models without explicitly representing the global transition system. To avoid the state-space explosion phenomenon, APMC gives an accurate approximation of the satisfaction probability of the property instead of the exact value, but using only a very small amount of memory. The version of APMC we present in this paper can now handle efficiently both discrete and continuous time probabilistic systems. |
||
| + | | lrdeprojects = APMC |
||
| type = inproceedings |
| type = inproceedings |
||
| id = herault.06.qest |
| id = herault.06.qest |
||
| Line 33: | Line 34: | ||
The version of APMC we present in this paper can now handle |
The version of APMC we present in this paper can now handle |
||
efficiently both discrete and continuous time probabilistic |
efficiently both discrete and continuous time probabilistic |
||
| − | systems.<nowiki>}</nowiki> |
+ | systems.<nowiki>}</nowiki>, |
| + | lrdeprojects = <nowiki>{</nowiki>APMC<nowiki>}</nowiki> |
||
<nowiki>}</nowiki> |
<nowiki>}</nowiki> |
||
Revision as of 18:07, 4 November 2013
- Authors
- Thomas Hérault, Richard Lassaigne, Sylvain Peyronnet
- Where
- Proceedings of Qest 2006
- Type
- inproceedings
- Projects
- APMC
- Date
- 2006-01-01
Abstract
In this paper, we give a brief overview of APMC (Approximate Probabilistic Model Checker). APMC is a model checker that implements approximate probabilistic verification of probabilistic systems. It is based on Monte-Carlo method and the theory of randomized approximation schemes and allows to verify extremely large models without explicitly representing the global transition system. To avoid the state-space explosion phenomenon, APMC gives an accurate approximation of the satisfaction probability of the property instead of the exact value, but using only a very small amount of memory. The version of APMC we present in this paper can now handle efficiently both discrete and continuous time probabilistic systems.
Bibtex (lrde.bib)
@InProceedings{ herault.06.qest,
author = {Thomas H\'erault and Richard Lassaigne and Sylvain
Peyronnet},
title = {{APMC 3.0}: Approximate verification of Discrete and
Continuous Time Markov Chains},
booktitle = {Proceedings of Qest 2006},
year = 2006,
pages = {129--130},
project = {APMC},
abstract = {In this paper, we give a brief overview of APMC
(Approximate Probabilistic Model Checker). APMC is a model
checker that implements approximate probabilistic
verification of probabilistic systems. It is based on
Monte-Carlo method and the theory of randomized
approximation schemes and allows to verify extremely large
models without explicitly representing the global
transition system. To avoid the state-space explosion
phenomenon, APMC gives an accurate approximation of the
satisfaction probability of the property instead of the
exact value, but using only a very small amount of memory.
The version of APMC we present in this paper can now handle
efficiently both discrete and continuous time probabilistic
systems.},
lrdeprojects = {APMC}
}