How languages are learned is one of the deepest mysteries of cognitive science. This question can be addressed from multiple perspectives. This position paper considers two of them: (1) How do people learn spatial language? (2) Given the wide range of spatial terms in language, how might we bootstrap the linguistic capabilities of intelligent systems that need spatial language to achieve wide and accurate coverage? We discuss each question in turn.
@InProceedings{forbus:DagSemProc.10131.2, author = {Forbus, Kenneth D.}, title = {{How can spatial language be learned?}}, booktitle = {Spatial Representation and Reasoning in Language : Ontologies and Logics of Space}, pages = {1--3}, series = {Dagstuhl Seminar Proceedings (DagSemProc)}, ISSN = {1862-4405}, year = {2011}, volume = {10131}, editor = {John A. Bateman and Anthony G. Cohn and James Pustejovsky}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.10131.2}, URN = {urn:nbn:de:0030-drops-27336}, doi = {10.4230/DagSemProc.10131.2}, annote = {Keywords: Sketch understanding, analogy, spatial language, spatial reasoning} }
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