… apply RL or deep RL for maintenance planning and … maintenance planning problem and
RL and DRL-based solutions. It also references other resources that can help to gain a deeper …

… Although DRL methods along with MDP developed for maintenance planning problems
in some applications, to the best of our knowledge, railroad infrastructure, specifically track, …

… a joint maintenance planning problem by considering several decisions simultaneously,
including workforce planning, workforce training, and spare parts inventory management. We …

… applicable to infrastructure problems beyond inspection and maintenance planning, such …
inspection and maintenance planning methods is that the decision-making problem, despite its …

… In the maintenance planning problem, the environment can be considered as the natural …
To handle the complex maintenance planning problem, a machine learning method, DRL, …

… novel distributed deep loop Q network multiagent deep reinforcement … maintenance plan
and improve the accuracy and intelligence level of making power equipment maintenance plan. …

… In this study, we used a deep Q network approach in order to solve the problem. The Total
cost and DQN loss shown in Figure 2 tend to remain in a narrow band after a small number of …

… In this application setting, the learned policy is referred to as rehabilitation/maintenance
plan. We study the problem of rehabilitation planning via online and offline DRL approaches, …

… Recently, more practical issues have been considered in the CBM planning, eg, the impact
of degradation behavior, setup time and measurement accuracy [11], the age and state …

… maintenance training with unpredictable disassembly targets. As a promising method for
settling dynamic and stochastic problems, deep reinforcement … This study introduces the deep Q-…