Grounding Strategic Conversation: Using negotiation dialogues to predict trades in a win-lose game

Anais Cadilhac, Nicholas Asher, Farah Benemara, Alex Lascarides

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper describes a method that predicts which trades players execute during a win-lose game. Our method uses data collected from chat negotiations of the game <em>The Settlers of Catan</em> and exploits the conversation to construct dynamically a partial model of each player's preferences. This in turn yields equilibrium trading moves via principles from game theory. We compare our method against four baselines and show that tracking how preferences evolve through the dialogue and reasoning about equilibrium moves are both crucial to success.
Original languageEnglish
Title of host publicationProceedings of Empirical Methods in Natural Language Processing (EMNLP)
Place of PublicationSeattle
Pages357-368
Number of pages9
Publication statusPublished - 2013

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