Abstract
The paper presents PALERMO — a planner used to answer queries in the SEIDAM information system for forestry. The information system is characterized by the large complexity of software and data sets involved. PALERMO uses previously answered queries and several planning techniques to put together plans that, when executed, produce products by calling the appropriate systems (GIS, image analysis, database, models) and ensures the proper flow on information between them. Experimental investigation of several planning techniques indicates that analogical planning cuts down the search involved in planning without experiencing the utility problem.
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© 1996 Springer-Verlag Berlin Heidelberg
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Charlebois, D., Goodenough, D.G., Matwin, S., (Pal) Bhogal, A.S., Barclay, H. (1996). Planning and learning in a natural resource information system. In: McCalla, G. (eds) Advances in Artifical Intelligence. Canadian AI 1996. Lecture Notes in Computer Science, vol 1081. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61291-2_51
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DOI: https://doi.org/10.1007/3-540-61291-2_51
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