We provide an efficient algorithm for multi-objective model-checking problems on Markov decision processes (MDPs) with multiple cost structures. The key problem at hand is to check whether there exists a scheduler for a given MDP such that all objectives over cost vectors are fulfilled. Reachability and expected cost objectives are covered and can be mixed. Empirical evaluation shows the algorithm’s scalability. We discuss the need for output beyond Pareto curves and exploit the available information from the algorithm to support decision makers.
|Title of host publication||Proceedings of the 24th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2018)|
|Editors||Dirk Beyer, Marieke Huisman|
|Place of Publication||Cham|
|Number of pages||20|
|Publication status||Published - 2018|
|Name||Lecture Notes in Computer Science|