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| A Cooperative Deployment Algorithm for Marine Fleet Detection Nodes Based on Constrained Reinforcement Learning |
| DU Junnan， SHUAI Yixian， CHEN Ding， WANG Min， ZHOU Jinpeng |
| Shanghai Electro-Mechanical Engineering Institute， Shanghai 201109， China |
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Abstract This paper proposed a cooperative deployment algorithm for naval fleet detection nodes based on constrained reinforcement learning to address the coordinated deployment of detection nodes in naval fleet formations. First, the method of dividing grids with regular hexagons was employed to design the grid. The battlefield space was modelled based on the battlefield space feature expression optimisation model of the graph neural network. Then, taking the formation's overall detection range and interception depth as the main optimisation objectives and considering constraints such as formation combat damage, deployment formation, ship orientation, and communication range, an intelligent agent model for the collaborative deployment of detection nodes was produced. Finally, the collaboration deployment intelligent agent model is trained in the air defense combat scenario of the US naval vessel formation. The simulation results show that the fleet deployment positions are optimized by the cooperative deployment algorithm proposed in this paper and the overall interception effectiveness of the fleet is improved by 13.1%.
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Received: 20 January 2025
Published: 15 July 2025
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2025, Vol. 8 
