2 papers
cs.LG2023
POMDP inference and robust solution via deep reinforcement learning: An application to railway optimal maintenance
Giacomo Arcieri, Cyprien Hoelzl, Oliver Schwery +3
Partially Observable Markov Decision Processes (POMDPs) can model complex sequential decision-making problems under stochastic and uncertain environments. A main reason hindering t…
cs.AI2022
Bridging POMDPs and Bayesian decision making for robust maintenance planning under model uncertainty: An application to railway systems
Giacomo Arcieri, Cyprien Hoelzl, Oliver Schwery +3
Structural Health Monitoring (SHM) describes a process for inferring quantifiable metrics of structural condition, which can serve as input to support decisions on the operation an…