Modeling human-agent interaction using Bayesian network technique

Authors:
Yukiko Nakano;Kazuyoshi Murata;Mika Enomoto;Yoshiko Arimoto;Yasuhiro Asa;Hirohiko Sagawa
Affiliations:
Tokyo University of Agri-culture and Technology, Koganei-shi, Tokyo, Japan;Tokyo University of Agri-culture and Technology, Koganei-shi, Tokyo, Japan;Tokyo University of Agri-culture and Technology, Koganei-shi, Tokyo, Japan;Tokyo University of Technology, Hachioji, Tokyo, Japan;Central Research Laboratory, Hitachi, Ltd., Kokub-unji-shi, Tokyo, Japan;Central Research Laboratory, Hitachi, Ltd., Kokub-unji-shi, Tokyo, Japan
Venue:
JSAI'07 Proceedings of the 2007 conference on New frontiers in artificial intelligence
Year:
2007

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The lumière project: Bayesian user modeling for inferring the goals and needs of software users

UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence

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Abstract

Task manipulation is direct evidence of understanding, and speakers adjust their utterances that are in progress by monitoring listener's task manipulation. Aiming at developing animated agents that control multimodal instruction dialogues by monitoring users' task manipulation, this paper presents a probabilistic model of fine-grained timing dependencies among multimodal communication behaviors. Our preliminary evaluation demonstrated that our model quite accurately judges whether the user understand the agent's utterances and predicts user's successful mouse manipulation, suggesting that the model is useful in estimating user's understanding and can be applied to determining the next action of an agent.