Researchers propose DRG-MAPPO, a hierarchical dynamic role-graph multi-agent reinforcement learning method aimed at improving tactical coordination for cooperative air combat. The work addresses the difficulty of achieving sophisticated tactical coordination in multi-agent reinforcement learning for autonomous air combat systems.
Multi-Agent Reinforcement Learning (MARL) has emerged as a pivotal paradigm for complex decision-making in autonomous systems and air combat. While MARL has demonstrated significant potential in air combat, achieving sophisticated tactical coordination remains a non-trivial challenge. This difficult
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