Grounding Natural Language References to Unvisited and Hypothetical Locations

Thomas Emrys Williams, Rehj Cantrell, Gordon Briggs, Paul W. Schermerhorn, Matthias Scheutz

AAAI 2013 pp. 947-953

doi:10.1609/AAAI.V27I1.8563 /aaai/2013/williams2013aaai-grounding/

Abstract

While much research exists on resolving spatial natural language references to known locations, little work deals with handling references to unknown locations. In this paper we introduce and evaluate algorithms integrated into a cognitive architecture which allow an agent to learn about its environ-ment while resolving references to both known and unknown locations. We also describe how multiple components in the architecture jointly facilitate these capabilities.

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Text

Williams et al. "Grounding Natural Language References to Unvisited and Hypothetical Locations." AAAI Conference on Artificial Intelligence, 2013. doi:10.1609/AAAI.V27I1.8563

Markdown

[Williams et al. "Grounding Natural Language References to Unvisited and Hypothetical Locations." AAAI Conference on Artificial Intelligence, 2013.](https://mlanthology.org/aaai/2013/williams2013aaai-grounding/) doi:10.1609/AAAI.V27I1.8563

BibTeX

@inproceedings{williams2013aaai-grounding,
  title     = {{Grounding Natural Language References to Unvisited and Hypothetical Locations}},
  author    = {Williams, Thomas Emrys and Cantrell, Rehj and Briggs, Gordon and Schermerhorn, Paul W. and Scheutz, Matthias},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2013},
  pages     = {947-953},
  doi       = {10.1609/AAAI.V27I1.8563},
  url       = {https://mlanthology.org/aaai/2013/williams2013aaai-grounding/}
}