Hierarchical Reinforcement Learning Framework for Stochastic Spaceflight Campaign Design

What is it about?

This paper develops a spaceflight mission designing framework which optimizes vehicle (spacecraft) design, resource deployment, and detailed space transportation scheduling at the same time, under the consideration of in-situ resource utilization in space and uncertain factors in mission scenario. This is enabled by the integrated framework of reinforcement learning and mixed-integer linear programming.

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Photo by Andy Holmes on Unsplash

Photo by Andy Holmes on Unsplash