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R3-[Q-Shape] pursues the development of techniques to efficiently and robustly solve complex spatial tasks and aim at advancing formal techniques to real-world problems. In particular, we investigate techniques of qualitative spatial representation and reasoning to obtain an adequate level of abstraction and effective means for a task at hand. Three ways to achieve abstractions are fostered: aspectualization, coarsening, and conceptual classification. We address navigation and recognition tasks by designing suitable underlying representations and neighborhood- and constraint-based reasoning methods.
See the Q-Shape project site for more information.
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