Planning, Inference and Pragmatics in Sequential Language Games
Transactions of the Association for Computational Linguistics2018Vol. 6, pp. 543–555
Citations Over TimeTop 10% of 2018 papers
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.
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