| Abstract: | Observations with NASA's Hubble Space Telescope (HST) are scheduled with the assistance of a long-range scheduling system (Spike) that was developed using artificial intelligence techniques. In earlier papers, we have described the system architecture and the constraint representation and propagation mechanisms. In this paper we describe the development of highlevel automated scheduling tools, including tools based on constraint satisfaction techniques and neural networks. The performance of these tools in scheduling HST observations is discussed. |
