Planning, Inference and Pragmatics in Sequential Language Games

Fereshte Khani, Noah D. Goodman, Percy Liang


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:
Venue:
TACL
SIG:
Publisher:
Note:
Pages:
543–555
Language:
URL:
https://www.aclweb.org/anthology/Q18-1037
DOI:
10.1162/tacl_a_00037
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PDF:
http://aclanthology.lst.uni-saarland.de/Q18-1037.pdf