Multi-Satellite Observation Task Allocation Method Based on Multi-Agent Deep Reinforcement Learning
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.
multi-agent systemdeep reinforcement learningmulti-satellite systemmulti-agent deep deterministic policy gradient(MADDPG)mission planning
国家科技期刊平台
NSTL
万方数据
维普
