Maintenance planning of networked multi-asset systems is a complex problem due to the
inherent individual and collective asset constraints and dynamics as well as the size of the …

Reinforcement Learning (RL) has become a critical tool for optimization challenges within
automation, leading to significant advancements in several areas. This review article …

The purpose of this paper is to analyse the effect of different maintenance strategies for a
network of assets whose condition deteriorates progressively along the time. We propose …

This thesis investigates the application of Deep Multi-Agent Reinforcement Learning
(DMARL) to problems within telecommunications and logistics. These sectors are exemplary …