A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Interpretable Team Estimation in Werewolf Games using Similarity-based Decision Tree of Utterances
発言の類似性に基づく決定木を用いた人狼ゲーム陣営推定における根拠の提示
JSAI Technical Report, SIG-KBS
発言の類似性に基づく決定木を用いた人狼ゲーム陣営推定における根拠の提示
Preserved Fulltext
The Werewolf game is a conversation-based multi-player incomplete information game, and it is recognized as a new standard game problem in AI field. It is key issues for the development of AI agent that can play the werewolf games naturally with human players to implement the ability on explaining the grounds of estimations for other players' roles and intentions behind their behaviors. In this paper, as a first step towards the above goal, we propose a decision tree-based role estimation model
doi:10.11517/jsaikbs.122.0_02
fatcat:udqe7u5smfdulhpion4eokoyde