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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 Integrated Computer Systems. Linköping University, Faculty of Science & Engineering. (KPLAB - Knowledge Processing Lab)
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated 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) / [ed] Dale Schuurmans, Dale Wellman, AAAI Press, 2016, Vol. 2, p. 957-963Conference paper, Published 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
AAAI Press, 2016. Vol. 2, p. 957-963
Series
Proceedings of the AAAI Conference on Artificial Intelligence, ISSN 2159-5399, E-ISSN 2374-3468
Keywords [en]
stream reasoning, spatial reasoning, qualitative reasoning
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-124440ISI: 000485474200133ISBN: 978-1-57735-762-9 (print)OAI: oai:DiVA.org:liu-124440DiVA, id: 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 CommunicationsAvailable from: 2016-02-01 Created: 2016-02-01 Last updated: 2020-06-29

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de Leng, DanielHeintz, Fredrik

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