Before revision:  We show that under mild assumptions, optimal values of parameters can be efficiently approximated using translation to a Markov decision process (MDP) whose actions correspond to discretized values of these parameters . Even though the translation is theoretically efficient, we also provide heuristics that further decreases the size of the MDP depending on properties of the continuous-time model .
After revision:  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 . Even though the translation is theoretically efficient, we also provide heuristics that further decreases the size of the MDP depending on properties of the continuous-time model .