### Abstract

Original language | Undefined |
---|---|

Place of Publication | Enschede |

Publisher | Elektrotechniek, Wiskunde & Informatica |

Number of pages | 30 |

Publication status | Published - 2004 |

### Publication series

Name | 1381-3625 |
---|---|

Publisher | University of Twente, Centre for Telematics and Information Technology (CTIT) |

No. | 03-50 |

### Keywords

- METIS-221438
- IR-49256

### Cite this

*Efficient computation of time-bounded reachability probabilities in uniform continuous-time Markov decision processes*. (1381-3625; No. 03-50). Enschede: Elektrotechniek, Wiskunde & Informatica.

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*Efficient computation of time-bounded reachability probabilities in uniform continuous-time Markov decision processes*. 1381-3625, no. 03-50, Elektrotechniek, Wiskunde & Informatica, Enschede.

**Efficient computation of time-bounded reachability probabilities in uniform continuous-time Markov decision processes.** / Baier, Christel; Haverkort, Boudewijn R.H.M.; Hermanns, H.; Katoen, Joost P.

Research output: Book/Report › Report › Professional

TY - BOOK

T1 - Efficient computation of time-bounded reachability probabilities in uniform continuous-time Markov decision processes

AU - Baier, Christel

AU - Haverkort, Boudewijn R.H.M.

AU - Hermanns, H.

AU - Katoen, Joost P.

PY - 2004

Y1 - 2004

N2 - A continuous-time Markov decision process (CTMDP) is a generalization of a continuous-time Markov chain in which both probabilistic and nondeterministic choices co-exist. This paper presents an efficient algorithm to compute the maximum (or minimum) probability to reach a set of goal states within a given time bound in a uniform CTMDP, i.e., a CTMDP in which the delay time distribution per state visit is the same for all states. We prove that these probabilities coincide for (time-abstract) history-dependent and Markovian schedulers that resolve nondeterminism either deterministically or in a randomized way.

AB - A continuous-time Markov decision process (CTMDP) is a generalization of a continuous-time Markov chain in which both probabilistic and nondeterministic choices co-exist. This paper presents an efficient algorithm to compute the maximum (or minimum) probability to reach a set of goal states within a given time bound in a uniform CTMDP, i.e., a CTMDP in which the delay time distribution per state visit is the same for all states. We prove that these probabilities coincide for (time-abstract) history-dependent and Markovian schedulers that resolve nondeterminism either deterministically or in a randomized way.

KW - METIS-221438

KW - IR-49256

M3 - Report

T3 - 1381-3625

BT - Efficient computation of time-bounded reachability probabilities in uniform continuous-time Markov decision processes

PB - Elektrotechniek, Wiskunde & Informatica

CY - Enschede

ER -