著者

箕輪 峻 狩野 芳伸

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.35, no.1, pp.DSI-F_1-13, 2020-01-01 (Released:2020-01-01)

参考文献数

17

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Recently, end-to-end learning is frequently used to implement dialogue systems. However, existing systems still suffer from issues to handle complex dialogues. In this paper, we target on the conversation game “Mafia”, which requires players to make consistent and complex communications. We propose a middle language expression and a converter from natural language input. We implemented our dialogue system to play the Mafia game with humans and other automatic agents. Our evaluation on the play shows that our middle language increases conversion coverage.