Abstract
One of the critical issues confronted in doing logical inference on large spatiotemporal knowledge bases is the fact that most real-world logical relationships are contextual in nature. Contextuality must be explicitly taken into account to make real-world inference tractable. This is one of the issues with which formal-logic-based AI has traditionally had the most difficulty. In this chapter we briefly explore the notion of contextual inference and the key approaches that have been taken.
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© 2011 Atlantis Press
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Goertzel, B., Geisweiller, N., Coelho, L., Janicic, P., Pennachin, C. (2011). Representing and Reasoning on Contextual Knowledge. In: Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference. Atlantis Thinking Machines, vol 1. Atlantis Press. https://doi.org/10.2991/978-94-91216-11-4_7
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DOI: https://doi.org/10.2991/978-94-91216-11-4_7
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Publisher Name: Atlantis Press
Print ISBN: 978-94-91216-10-7
Online ISBN: 978-94-91216-11-4
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