We provide a memory-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. We cover multi-objective reachability and expected cost objectives, and combinations thereof. We further transfer approaches for computing quantiles over single cost bounds to the multi-cost case and highlight the ensuing challenges. An empirical evaluation shows the scalability of our new approach both in terms of memory consumption and runtime. We discuss the need for more detailed visual presentations of results beyond Pareto curves and present a first visualisation approach that exploits all the available information from the algorithm to support decision makers.

中文翻译：

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MDP中的多成本有界权衡分析

我们为具有多个成本结构的马尔可夫决策过程 (MDP) 上的多目标模型检查问题提供了一种内存高效的算法。手头的关键问题是检查是否存在给定 MDP 的调度程序，以便满足成本向量上的所有目标。我们涵盖了多目标可达性和预期成本目标，以及它们的组合。我们进一步将计算单成本界限的分位数方法转移到多成本情况，并强调了随之而来的挑战。实证评估显示了我们的新方法在内存消耗和运行时间方面的可扩展性。