Abstract
This paper describes how language is grounded by a comprehension system called Lucia within a robotic agent called Rosie that can manipulate objects and navigate indoors. The whole system is built within the Soar cognitive architecture and uses Embodied Construction Grammar (ECG) as a formalism for describing linguistic knowledge. Grounding is performed using knowledge from the grammar itself, from the linguistic context, from the agent's perception, and from an ontology of long-term knowledge about object categories and properties and actions the agent can perform. The paper also describes a benchmark corpus of 200 sentences in this domain, along with test versions of the world model and ontology, and gold-standard meanings for each of the sentences. The benchmark is contained in the supplemental materials.
Cite
CITATION STYLE
Lindes, P., Mininger, A., Kirk, J. R., & Laird, J. E. (2017). Grounding language for interactive task learning. In Proceedings of the 1st Workshop on Language Grounding for Robotics, RoboNLP 2017 at the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 (pp. 1–9). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w17-2801
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