Abstract
We discuss the problems of spatio-temporal reasoning in the context of hierarchical information maps and approximate reasoning networks (AR networks). Hierarchical information maps are used for representation of domain knowledge about objects, their parts, and their dynamical changes. They are constructed out of information maps connected by some spatial relations. Each map describes changes (e.g., in time) of states corresponding to some parts of complex objects. We discuss the details of defining relations between levels of hierarchical information maps as well as between parts satisfying some additional constraints, e.g. spatial ones.
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Skowron, A., Synak, P. (2005). Hierarchical Information Maps. In: Ślęzak, D., Wang, G., Szczuka, M., Düntsch, I., Yao, Y. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2005. Lecture Notes in Computer Science(), vol 3641. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11548669_64
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DOI: https://doi.org/10.1007/11548669_64
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28653-0
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