Abstract
We study sequential language games in which two players, each with private information, communicate to achieve a common goal. In such games, a successful player must (i) infer the partner’s private information from the partner’s messages, (ii) generate messages that are most likely to help with the goal, and (iii) reason pragmatically about the partner’s strategy. We propose a model that captures all three characteristics and demonstrate their importance in capturing human behavior on a new goal-oriented dataset we collected using crowdsourcing.- Anthology ID:
- Q18-1037
- Volume:
- Transactions of the Association for Computational Linguistics, Volume 6
- Month:
- Year:
- 2018
- Address:
- Cambridge, MA
- Editors:
- Lillian Lee, Mark Johnson, Kristina Toutanova, Brian Roark
- Venue:
- TACL
- SIG:
- Publisher:
- MIT Press
- Note:
- Pages:
- 543–555
- Language:
- URL:
- https://aclanthology.org/Q18-1037
- DOI:
- 10.1162/tacl_a_00037
- Cite (ACL):
- Fereshte Khani, Noah D. Goodman, and Percy Liang. 2018. Planning, Inference and Pragmatics in Sequential Language Games. Transactions of the Association for Computational Linguistics, 6:543–555.
- Cite (Informal):
- Planning, Inference and Pragmatics in Sequential Language Games (Khani et al., TACL 2018)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/Q18-1037.pdf
- Code
- worksheets/0x052129c7