Mean Payoff Optimization for Systems of Periodic Service and Maintenance

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Authors

KLAŠKA David KUČERA Antonín MUSIL Vít ŘEHÁK Vojtěch

Year of publication 2023
Type Article in Proceedings
Conference Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI 2023,
MU Faculty or unit

Faculty of Informatics

Citation
Web Paper URL
Doi http://dx.doi.org/10.24963/ijcai.2023/598
Keywords Periodic Maintenance; strategy synthesis
Attached files
Description Consider oriented graph nodes requiring periodic visits by a service agent. The agent moves among the nodes and receives a payoff for each completed service task, depending on the time elapsed since the previous visit to a node. We consider the problem of finding a suitable schedule for the agent to maximize its long-run average payoff per time unit. We show that the problem of constructing an epsilon-optimal schedule is PSPACE-hard for every fixed non-negative epsilon, and that there exists an optimal periodic schedule of exponential length. We propose randomized finite-memory (RFM) schedules as a compact description of the agent's strategies and design an efficient algorithm for constructing RFM schedules. Furthermore, we construct deterministic periodic schedules by sampling from RFM schedules.
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