Grounding Natural Language References to Unvisited and Hypothetical Locations

Authors

  • Thomas Williams Tufts University
  • Rehj Cantrell Indiana University
  • Gordon Briggs Tufts University
  • Paul Schermerhorn Indiana University
  • Matthias Scheutz Tufts University

DOI:

https://doi.org/10.1609/aaai.v27i1.8563

Keywords:

spatial reference resolution, human-robot interaction, natural language processing

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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Published

2013-06-30

How to Cite

Williams, T., Cantrell, R., Briggs, G., Schermerhorn, P., & Scheutz, M. (2013). Grounding Natural Language References to Unvisited and Hypothetical Locations. Proceedings of the AAAI Conference on Artificial Intelligence, 27(1), 947-953. https://doi.org/10.1609/aaai.v27i1.8563