In this article, a GRU-Multi-agent Proximal Policy Optimization (GRU-MAPPO) algorithm was proposed to address unmanned aerial vehicle (UAV) cooperative air combat decision-making problem. This algorithm adds a layer of GRU to the Actor-Critic network framework, uses update gate to extract the historical temporal information and enhance situational awareness. Finally, experiments in our constructed UAV cooperative air combat environment demonstrate that UAVs using the algorithm proposed in this article can learn effective strategies in air combat environments and achieve high win rates.
UAV Cooperative Air Combat Maneuvering Decision-Making Using GRU-MAPPO
18.06.2024
845517 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
UAV Swarm Cooperative Dynamic Target Search: A MAPPO-Based Discrete Optimal Control Method
DOAJ | 2024
|Maneuvering-decision analysis for air-to-air combat
British Library Online Contents | 1997
|Resource Baseline MAPPO for Multi-UAV Dog Fighting
Springer Verlag | 2022
|Cooperative Combat Decision-making Research for Multi UAVs
British Library Online Contents | 2018
|Intelligent Air Combat Maneuvering Decision Based on TD3 Algorithm
Springer Verlag | 2023
|