Qualitative Spatial and Temporal Reasoning: Current Status and Future Challenges
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Survey Track. Pages 4594-4601.
https://doi.org/10.24963/ijcai.2021/624
Keywords
- Knowledge representation and reasoning: General
Abstract
Qualitative Spatial & Temporal Reasoning (QSTR)
is a major field of study in Symbolic AI that deals
with the representation and reasoning of spatio-
temporal information in an abstract, human-like
manner. We survey the current status of QSTR
from a viewpoint of reasoning approaches, and
identify certain future challenges that we think
that, once overcome, will allow the field to meet
the demands of and adapt to real-world, dynamic,
and time-critical applications of highly active areas
such as machine learning and data mining.
@inproceedings{ijcai2021p624,
title = {Qualitative Spatial and Temporal Reasoning: Current Status and Future Challenges},
author = {Sioutis, Michael and Wolter, Diedrich},
booktitle = {Proceedings of the Thirtieth International Joint Conference on
Artificial Intelligence, {IJCAI-21}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Prof. Zhi-Hua Zhou},
pages = {4594--4601},
year = {2021},
month = {8},
note = {Survey Track},
doi = {10.24963/ijcai.2021/624},
url = {https://doi.org/10.24963/ijcai.2021/624},
}
TY - CPAPER TI - Qualitative Spatial and Temporal Reasoning: Current Status and Future Challenges AU - Sioutis, Michael AU - Wolter, Diedrich T2 - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2021 SP - 4594 EP - 4601 DO - 10.24963/ijcai.2021/624 UR - https://doi.org/10.24963/ijcai.2021/624 ER -Copied
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