Socially-Conditioned Task Reasoning For A Virtual Tutoring Agent

PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS (AAMAS' 18)(2018)

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摘要
Virtual agents have been shown to be more effective when incorporating social factors such as trust into task action selection. However, there has been less work on how virtual tutoring agents can incorporate social factors into pedagogical action selection. We propose and evaluate how a socially-conditioned task reasoner for a virtual pedagogical agent can incorporate both task and social factors into task reasoning. Our work contributes to the autonomous agent community by providing further evidence that incorporating information about dyadic social factors (e.g. rapport) can be beneficial for agents' task reasoning in the case of a tutoring agent.
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关键词
Socially-aware, pedagogical agent, rapport, RL-LSTM
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