Abstract
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 the ability to be taught reusable conditional procedures, the ability to be taught new knowledge about the world (concepts in an ontology) and 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.- Anthology ID:
- D18-2025
- Volume:
- Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
- Month:
- November
- Year:
- 2018
- Address:
- Brussels, Belgium
- Editors:
- Eduardo Blanco, Wei Lu
- Venue:
- EMNLP
- SIG:
- SIGDAT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 145–150
- Language:
- URL:
- https://aclanthology.org/D18-2025
- DOI:
- 10.18653/v1/D18-2025
- Cite (ACL):
- Igor Labutov, Shashank Srivastava, and Tom Mitchell. 2018. LIA: A Natural Language Programmable Personal Assistant. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 145–150, Brussels, Belgium. Association for Computational Linguistics.
- Cite (Informal):
- LIA: A Natural Language Programmable Personal Assistant (Labutov et al., EMNLP 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/D18-2025.pdf