Optimal Continuous Time Markov Decisions
| Authors | |
|---|---|
| Year of publication | 2015 |
| Type | Article in Proceedings |
| Conference | ATVA 2015 |
| MU Faculty or unit | |
| Citation | |
| Doi | http://dx.doi.org/10.1007/978-3-319-24953-7_12 |
| Field | Informatics |
| Keywords | Continuous time Markov decision process; time bounded reachability; uniformisation; experimental evaluation |
| Description | In the context of Markov decision processes running in continuous time, one of the most intriguing challenges is the efficient approximation of finite horizon reachability objectives. A multitude of sophisticated model checking algorithms have been proposed for this. However, no proper benchmarking has been performed thus far. This paper presents a novel and yet simple solution: an algorithm originally developed for a restricted subclass of models and a subclass of schedulers can be twisted so as to become competitive with the more sophisticated algorithms in full generality. As the second main contribution, we perform a comparative evaluation of the core algorithmic concepts on an extensive set of benchmarks varying over all key parameters: model size, amount of non-determinism, time horizon, and precision. |
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