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Shared Backbone PPO for Multi-UAV Communication Coverage with Connection Preservation

arXiv 2605.17999 ↗First posted 18 May 2026cs.AIcited by 0

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Abstract (arXiv)

This paper proposes a Shared Backbone Proximal Policy Optimization (Shared Backbone PPO) algorithm. By sharing the base module between the Actor and Critic networks, the algorithm achieves efficient training and improved performance. The algorithm is implemented in a connectivity-preserving multi-UAV swarm communication coverage task and compared with the standard PPO algorithm. Experimental results demonstrate that the proposed method achieves superior performance. Furthermore, a graph information aggregation module is incorporated into the model architecture to accommodate the communication conditions among agents. With the integration of this module, the algorithm remains effective, and the trained agent swarm exhibits a higher level of cooperation.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 22 references that are in the map. First posted on arXiv 18 May 2026.

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References · 5

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 9,379
  3. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,885
  4. 2013Playing Atari with Deep Reinforcement Learningcited by 3,274
  5. 2025A Differentiated Reward Method for Reinforcement Learning based Multi-Vehicle Cooperative Decision-Making Algorithmscited by 1

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  3. 2024Variations in Multi-Agent Actor-Critic Frameworks for Joint Optimizations in UAV Swarm Networks: Recent Evolution, Challenges, and Directions ↗
  4. 2025Towards Robust Multi-UAV Collaboration: MARL with Noise-Resilient Communication and Attention Mechanisms
  5. 2025Aerial Reliable Collaborative Communications for Terrestrial Mobile Users via Evolutionary Multi-Objective Deep Reinforcement Learning
  6. 2026UAV Swarming for Air-Ground ISAC via Cross-Region Cooperation ↗
  7. 2024Multi-UAV Multi-RIS QoS-Aware Aerial Communication Systems using DRL and PSO
  8. 2025Multi-Agent Deep Reinforcement Learning for Collaborative UAV Relay Networks under Jamming Atatcks