Synthesis of Pareto-optimal Policies for Continuous-Time Markov Decision Processes

Abstract

We present a work-in-progress method for the synthesis of continuous-time Markov decision process (CTMDP) policies-an important problem not handled by current probabilistic model checkers. The policies synthesised by this method correspond to configurations of software systems or software controllers of cyber-physical systems (CPS) that satisfy predefined nonfunctional constraints and are Pareto-optimal with respect to a set of optimisation objectives. We illustrate the effectiveness of our method by using it to synthesise optimal configurations for a client-server system, and optimal controllers for a driverattention management CPS.