Optimizing Performance of Continuous-Time Stochastic Systems using Timeout Synthesis
Performance
2016-04-18 v4
Abstract
We consider parametric version of fixed-delay continuous-time Markov chains (or equivalently deterministic and stochastic Petri nets, DSPN) where fixed-delay transitions are specified by parameters, rather than concrete values. Our goal is to synthesize values of these parameters that, for a given cost function, minimise expected total cost incurred before reaching a given set of target states. We show that under mild assumptions, optimal values of parameters can be effectively approximated using translation to a Markov decision process (MDP) whose actions correspond to discretized values of these parameters.
Cite
@article{arxiv.1407.4777,
title = {Optimizing Performance of Continuous-Time Stochastic Systems using Timeout Synthesis},
author = {Tomáš Brázdil and Ľuboš Korenčiak and Jan Krčál and Petr Novotný and Vojtěch Řehák},
journal= {arXiv preprint arXiv:1407.4777},
year = {2016}
}