共享主干网络提升多无人机通信覆盖效率
Shared Backbone PPO for Multi-UAV Communication Coverage with Connection Preservation
- 共享策略与价值网络主干，加速训练并提升性能
- 在保持连接性的前提下，通信覆盖率显著优于标准PPO
- 引入图信息聚合模块，增强多智能体协作能力
本文提出一种共享主干近端策略优化（Shared Backbone PPO）算法。通过在策略网络与价值网络间共享基础模块，实现高效训练并提升性能。该算法应用于保持连通性的多无人机编队通信覆盖任务，并与标准PPO算法进行对比。实验结果表明，所提方法表现更优。此外，在模型架构中引入图信息聚合模块，以适应智能体间的通信条件。融合该模块后，算法仍保持有效性，且训练后的智能体群表现出更高水平的协作能力。
原文摘要 · Abstract (English)
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.
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