We present LIA, an intelligent personal assistant that can be programmed using natural language. Our system demonstrates multiple competencies towards learning from human-like interactions. These include (i) the ability to be taught reusable conditional procedures, (ii) ability to be taught new knowledge about the world (concepts in an ontology) and (iii) the ability to be taught how to ground that knowledge in a set of sensors and effectors. Building such a system highlights design questions regarding the overall architecture that such an agent should have, as well as questions about parsing and grounding language in situational contexts. We outline key properties of this architecture, and demonstrate a prototype that embodies them in the form of a personal assistant on an Android device.
CITATION STYLE
Labutov, I., Srivastava, S., & Mitchell, T. (2018). LIA: A natural language programmable personal assistant. In EMNLP 2018 - Conference on Empirical Methods in Natural Language Processing: System Demonstrations, Proceedings (pp. 145–150). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/d18-2025
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