Maintaining knowledge about temporal intervals
Communications of the ACM
Computational Properties of Qualitative Spatial Reasoning: First Results
KI '95 Proceedings of the 19th Annual German Conference on Artificial Intelligence: Advances in Artificial Intelligence
Region connection calculus: its models and composition table
Artificial Intelligence
On Topological Consistency and Realization
Constraints
Computational Geometry: Algorithms and Applications
Computational Geometry: Algorithms and Applications
RCC8 binary constraint network can be consistently extended
Artificial Intelligence
Qualitative constraint satisfaction problems: An extended framework with landmarks
Artificial Intelligence
RR'13 Proceedings of the 7th international conference on Web Reasoning and Rule Systems
Multi-granularity and metric spatial reasoning
Expert Systems with Applications: An International Journal
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Consistency checking plays a central role in qualitative spatial and temporal reasoning. Given a set of variables V, and a set of constraints Γ taken from a qualitative calculus (e.g. the Interval Algebra (IA) or RCC-8), the aim is to decide if Γ is consistent. The consistency problem has been investigated extensively in the literature. Practical applications e.g. urban planning often impose, in addition to those between undetermined entities (variables), constraints between determined entities (constants or landmarks) and variables. This paper introduces this as a new class of qualitative constraint satisfaction problems, and investigates the new consistency problem in several well-known qualitative calculi, e.g. IA, RCC-5, and RCC-8. We show that the usual local consistency checking algorithm works for IA but fails in RCC-5 and RCC-8. We further show that, if the landmarks are represented by polygons, then the new consistency problem of RCC-5 is tractable but that of RCC-8 is NP-complete.