Name
Abstract | ||
|---|---|---|
Markov automata combine continuous time, probabilistic transitions, and nondeterminism in a single model. They represent an important and powerful way to model a wide range of complex real-life systems. However, such models tend to be large and difficult to handle, making abstraction and abstraction refinement necessary. In this paper we present an abstraction and abstraction refinement technique for Markov automata, based on the game-based and menu-based abstraction of probabilistic automata. First experiments show that a significant reduction in size is possible using abstraction. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.4204/EPTCS.154.4 | ELECTRONIC PROCEEDINGS IN THEORETICAL COMPUTER SCIENCE |
Field | DocType | Issue |
Abstraction,Computer science,Markov chain,Automaton,Algorithm,Theoretical computer science,Abstraction refinement,Stochastic game | Journal | 154 |
ISSN | Citations | PageRank |
2075-2180 | 3 | 0.38 |
References | Authors | |
21 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| bettina braitling | 1 | 60 | 4.64 |
| Luis María Ferrer Fioriti | 2 | 3 | 0.38 |
| Hassan Hatefi | 3 | 78 | 5.38 |
| Ralf Wimmer | 4 | 407 | 34.28 |
| Bernd Becker | 5 | 855 | 73.74 |
| Holger Hermanns | 6 | 3418 | 229.22 |