Constraint propagation algorithms for temporal reasoning: a revised report
Readings in qualitative reasoning about physical systems
From local to global consistency
Artificial Intelligence
Reasoning about qualitative temporal information
Artificial Intelligence - Special volume on constraint-based reasoning
Complexity and algorithms for reasoning about time: a graph-theoretic approach
Journal of the ACM (JACM)
Maintaining knowledge about temporal intervals
Communications of the ACM
A simple way to improve path consistency processing in interval algebra networks
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
A new proof of tractability for 0RD-horn relations
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
FroCoS '02 Proceedings of the 4th International Workshop on Frontiers of Combining Systems
A constraint satisfaction framework for executing perceptions and actions in diagrammatic reasoning
Journal of Artificial Intelligence Research
CASL specifications of qualitative calculi
COSIT'05 Proceedings of the 2005 international conference on Spatial Information Theory
Applied Ontology
Applied Ontology
Qualitative Spatial Representation and Reasoning: An Overview
Fundamenta Informaticae - Qualitative Spatial Reasoning
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Information about the relative size of spatial regions is often easily accessible and, when combined with other types of spatial information, it can be practically very useful. In this paper we combine a simple framework for reasoning about qualitative size relations with the Region Connection Calculus RCC-8, a widely studied approach for qualitative spatial reasoning with topological relations. Reasoning about RCC-8 relations is NP-hard, but a large maximal tractable subclass of RCC-8 called H8 was identified. Interestingly, any constraint in RCC-8 - H8 can be consistently reduced to a constraint in H8, when an appropriate size constraint between the spatial regions is supplied. We propose an O(n3) time path-consistency algorithm based on a novel technique for combining RCC-8 constraints and relative size constraints, where n is the number of spatial regions. We prove its correctness and completeness for deciding consistency when the input contains topological constraints in H8. We also provide results on finding a consistent scenario in O(n3) time both for combined topological and relative size constraints, and for topological constraints alone. This is an O(n2) improvement over the known methods.