Combining Topological and Directional Information for Spatial Reasoning
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 435-439.
Abstract
Current research on qualitative spatial representation and reasoning usually focuses on one single aspect of space. However, in real world applications, several aspects are often involved together. This paper extends the well-known RCC8 constraint language to deal with both topological and directional information, and then investigates the interaction between the two kinds of information. Given a topological (RCC8) constraint network and a directional constraint network, we ask when the joint network is satisfiable. We show that when the topological network is over one of the three maximal tractable subclasses of RCC8, the problem can be reduced into satisfiability problems in the RCC8 algebra and the rectangle algebra (RA). Therefore, reasoning techniques developed for RCC8 and RA can be used to solve the satisfiability problem of a joint network.
@inproceedings{ijcai2007p68,
title = {Combining Topological and Directional Information for Spatial Reasoning},
author = {Li, Sanjiang},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {435--439},
year = {2007},
url = {https://ijcai.org/proceedings/2007/68},
}
TY - CPAPER TI - Combining Topological and Directional Information for Spatial Reasoning AU - Li, Sanjiang T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 435 EP - 439 UR - https://ijcai.org/proceedings/2007/68 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: