Designing Low-Thrust Transfers near Earth–Moon L2 via Multi-Objective Reinforcement Learning

What is it about?

Multi-Reward Proximal Policy Optimization is developed and used to construct low-thrust transfers for a spacecraft in a multi-body system. These transfers are approximately validated using a traditional optimization scheme. Finally, a preliminary investigation into the influence of the hyperparameter selection is performed.

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