Publication details

Qualitative Controller Synthesis for Consumption Markov Decision Processes

Authors

BLAHOUDEK František BRÁZDIL Tomáš NOVOTNÝ Petr ORNIK Melkior THANGEDA Pranay TOPCU Ufuk

Year of publication 2020
Type Article in Proceedings
Conference Computer Aided Verification - 32nd International Conference, CAV 2020, Los Angeles, CA, USA, July 21-24, 2020, Proceedings, Part {II}
MU Faculty or unit

Faculty of Informatics

Citation
Doi http://dx.doi.org/10.1007/978-3-030-53291-8\_22
Keywords decision making; Markov decision processes; controller synthesis; resource constraints
Description Consumption Markov Decision Processes (CMDPs) are probabilistic decision-making models of resource-constrained systems. In a CMDP, the controller possesses a certain amount of a critical resource, such as electric power. Each action of the controller can consume some amount of the resource. Resource replenishment is only possible in special reload states, in which the resource level can be reloaded up to the full capacity of the system. The task of the controller is to prevent resource exhaustion, i.e. ensure that the available amount of the resource stays non-negative, while ensuring an additional linear-time property. We study the complexity of strategy synthesis in consumption MDPs with almost-sure Büchi objectives. We show that the problem can be solved in polynomial time. We implement our algorithm and show that it can efficiently solve CMDPs modelling real-world scenarios.
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