An advanced multi-agent reinforcement learning framework of bridge maintenance policy formulation

HIGHLIGHTS

• who: Qi-Neng Zhou and collaborators from the Department of Civil Engineering, Hefei University of Technology, Hefei, China have published the research: An Advanced Multi-Agent Reinforcement Learning Framework of Bridge Maintenance Policy Formulation, in the Journal: Sustainability 2022, 14, x FOR PEER REVIEW of /2022/
• what: In this paper a multi-agent reinforcement learning framework was proposed to predict the deterioration process reasonably and achieve the optimal maintenance Using the regression-based optimization method the Markov transition matrix can better describe the uncertain transition process of bridge components in the maintenance year and the . . .
  

   

  

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