98 citations · 191 across the 6 of their papers we have counts for
3 papers · 1 filter
Graph-Based Inference and Topology-Aware Multi-Agent Reinforcement Learning for Large-Scale Railway Network Management
Giacomo Arcieri, Gregory Duthé, Christophe Muller +3
Modern infrastructure asset management constitutes a complex sequential decision-making problem, characterized by long planning horizons and system-level interactions, such as spat…
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…
Value of structural health information in partially observable stochastic environments
C. P. Andriotis, K. G. Papakonstantinou, E. N. Chatzi
Efficient integration of uncertain observations with decision-making optimization is key for prescribing informed intervention actions, able to preserve structural safety of deteri…