Machine learning and planning for data management in forestry

The Seidam project uses an AI planning-based approach that combines three problem-solving methods-transformational analogy, derivational analogy and goal regression-to automatically answer forest-management queries. The project is conducted under NASA's Applied Information Systems Research Program. Seidam, which runs on a Sun Sparcstation using the Solaris 2.3 version of Unix, is a complex system that relies on extensive cooperation between expert systems and processing agents.