A maintenance planning framework using online and offline deep reinforcement learning

HIGHLIGHTS

  • who: Zaharah A. Bukhsh from the Eindhoven University of Technology, Eindhoven, The Netherlands have published the research work: A maintenance planning framework using online and offline deep reinforcement learning, in the Journal: (JOURNAL)
  • what: The authors demonstrate that DRL-based policies improve over standard preventive corrective and greedy planning alternatives. The authors design the elements for a DRL framework, including state definition, discrete actions, and reward function. - The authors show that the online DRL setup can learn a costeffective intervention policy compared to the traditional preventive, corrective, and greedy schedules. The work distinguishes itself from . . .

     

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