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

  • Authors:
  • Christel Baier;Holger Hermanns;Joost-Pieter Katoen;Boudewijn R. Haverkort

  • Affiliations:
  • University of Bonn, Römerstraße, Bonn, Germany;Saarland University, Department of Computer Science, Im Stadtwald, Saarbrücken, Germany and University of Twente, AE Enschede, The Netherlands;University of Twente, AE Enschede, The Netherlands;University of Twente, AE Enschede, The Netherlands

  • Venue:
  • Theoretical Computer Science - Tools and algorithms for the construction and analysis of systems (TACAS 2004)
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

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. It furthermore proves that these probabilities coincide for (time-abstract) history-dependent and Markovian schedulers that resolve nondeterminism either deterministically or in a randomized way.