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Qualitative Spatio-Temporal Stream Reasoning With Unobservable Intertemporal Spatial Relations Using Landmarks
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, Faculty of Science & Engineering. (KPLAB - Knowledge Processing Lab)
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, Faculty of Science & Engineering. (KPLAB - Knowledge Processing Lab)
2016 (English)In: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI), 2016Conference paper (Refereed)
Abstract [en]

Qualitative spatio-temporal reasoning is an active research area in Artificial Intelligence. In many situations there is a need to reason about intertemporal qualitative spatial relations, i.e. qualitative relations between spatial regions at different time-points. However, these relations can never be explicitly observed since they are between regions at different time-points. In applications where the qualitative spatial relations are partly acquired by for example a robotic system it is therefore necessary to infer these relations. This problem has, to the best of our knowledge, not been explicitly studied before. The contribution presented in this paper is two-fold. First, we present a spatio-temporal logic MSTL, which allows for spatio-temporal stream reasoning. Second, we define the concept of a landmark as a region that does not change between time-points and use these landmarks to infer qualitative spatio-temporal relations between non-landmark regions at different time-points. The qualitative spatial reasoning is done in RCC-8, but the approach is general and can be applied to any similar qualitative spatial formalism.

Place, publisher, year, edition, pages
2016.
Keyword [en]
stream reasoning, spatial reasoning, qualitative reasoning
National Category
Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-124440OAI: oai:DiVA.org:liu-124440DiVA: diva2:899389
Conference
Thirtieth AAAI Conference on Artificial Intelligence, 12-17 February 2016, Phoenix AZ, USA
Projects
CUGSNFFP6CUASCADICSELLIITCENIIT
Funder
CUGS (National Graduate School in Computer Science)eLLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications
Available from: 2016-02-01 Created: 2016-02-01 Last updated: 2016-02-08

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de Leng, DanielHeintz, Fredrik
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