| Abstract: | Since the concept of cooperative operation was put forward , all military powers have madegreat progress in the field of cooperative air combat , and coordination has become a multiplier to en.hance combat capability. In recent decades, as a modern intelligent method to solve sequence prob.lems , reinforcement learning has developed rapidly in various fields. However ,in the face of high-di.mensional variable problems ,the traditional single-agent reinforcement learning often performs poor.ly. Multi-agent reinforcement learning algorithms provide new possibilities for solving complex multi-dimensional problems. By analyzing the adaptability of multi-agent reinforcement learning algorithmprinciple , training paradigm and cooperative air combat, the future development direction of coopera-tive air combat and multi-agent reinforcement learning is proposed, which provides ideas for betterapplication of multi-agent reinforcement learning in cooperative air combat. |
