  The Frontier Development Lab (FDL) is a National Aeronautics and Space
Administration (NASA) machine learning program with the stated aim of
conducting artificial intelligence research for space exploration and all
humankind with support in the European program from the European Space Agency
(ESA). Interdisciplinary teams of researchers and data-scientists are brought
together to tackle a range of challenging, real-world problems in the
space-domain. The program primarily consists of a sprint phase during which
teams tackle separate problems in the spirit of 'coopetition'. Teams are given
a problem brief by real stakeholders and mentored by a range of experts. With
access to exceptional computational resources, we were challenged to make a
serious contribution within just eight weeks.
  Stated simply, our team was tasked with producing a system capable of
scheduling downloads from satellites autonomously. Scheduling is a difficult
problem in general, of course, complicated further in this scenario by
ill-defined objectives & measures of success, the difficulty of communicating
tacit knowledge and the standard challenges of real-world data. Taking a
broader perspective, spacecraft scheduling is a problem that currently lacks an
intelligent solution and, with the advent of mega-constellations, presents a
serious operational bottleneck for the missions of tomorrow.
