Qualitative Spatial Reasoning with Topological Information
Spatial knowledge representation and reasoning with spatial knowledge are relevant issues for many application areas such as robotics, geographical information systems, and computer vision. Exceeding purely quantitative approaches, more recently initiated qualitative approaches allow for dealing with spatial information on a more abstract level that is closer to the way humans think and speak.\ Starting out with the qualitative, topological constraint calculus RCC8 proposed by Randell, Cui,...
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Spatial knowledge representation and reasoning with spatial knowledge are relevant issues for many application areas such as robotics, geographical information systems, and computer vision. Exceeding purely quantitative approaches, more recently initiated qualitative approaches allow for dealing with spatial information on a more abstract level that is closer to the way humans think and speak.Starting out with the qualitative, topological constraint calculus RCC8 proposed by Randell, Cui, and Cohn, this work presents answers to a variety of open questions regarding RCC8. The open issues concerning computational properties are solved by exploiting a broad variety of results and methods from logic and theoretical computer science. Questions concerning practical performance are addressed by large-scale empirical computational experiments. The most impressive result is probably the complete classification of computational properties for all fragments of RCC8.
1Introduction12Background133Qualitative Spatial Representation and Reasoning314The Region Connection Calculus415Cognitive Properties of Topological Spatial Relations516Computational Properties of RCC-8657A Complete Analysis of Tractability in RCC-81178Empirical Evaluation of Reasoning with RCC-81319Representational Properties of RCC-815510Conclusions173AEnumeration of the Relations of the Maximal Tractable Subsets of RCC-8179References191Index201
