The scheduling of space transportation assets for multiple multiyear missions is addressed. The objectives of a space transportation architecture (STA) are outlined, and an approach to meeting them using the artificially intelligent model (AIM) is described. The context that influences the development of an STA is presented, and an overview of AIM, including the type of output that is provided to a user, is given. The representation and processing schemes used in AIM are discussed.
Knowledge-based scheduling
Wissensbasiertes Scheduling
1990
6 Seiten, 4 Quellen
Conference paper
English
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