Optimizing Performance of Continuous-Time Stochastic Systems using   Timeout Synthesis
  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. 
Tom\'a\v{s} Br\'azdil, \v{L}ubo\v{s} Koren\v{c}iak, Jan Kr\v{c}\'al,   Petr Novotn\'y, Vojt\v{e}ch \v{R}eh\'ak
cs.PF