基于多智能体深度强化学习的多星观测任务分配方法OA北大核心CSTPCD

To address the task allocation scenario under complex and constrained conditions in a multi-satellite environment,a multi-satellite autonomous decision-making observation task allocation algorithm is proposed.The algorithm uses a multi-agent deep reinforcement learning algorithm based on centralized training and distributed execution.The satellite agents trained by this algorithm have certain autonomous collaboration capabilities and the ability to independently achieve the efficient allocation of multi-satellite observation tasks even if there is no central decision-making node or communication restriction.