Unmanned aerial vehicle swarm cooperative decision-making for sead mission: a hierarchical multi-agent reinforcement learning approach

HIGHLIGHTS

• who: Unmanned Aerial Vehicle Swarm and collaborators from the Air Traffic Control and Navigation College, Air Force Engineering University, Xi'an, China have published the article: Unmanned Aerial Vehicle Swarm Cooperative Decision-Making for SEAD Mission: A Hierarchical Multi-Agent Reinforcement Learning Approach, in the Journal: (JOURNAL)
• what: This is the primary motivation of the present study. The authors propose a HMARL framework for UAV swarm cooperative decision-making.
• how: This paper proposes a learning (HMARL) method to solve the heterogeneous UAV decision-making problem for the typical suppression of enemy air defense . . .
  

   

  

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