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How Should Agents Ask Questions For Situated Learning? An Annotated Dialogue Corpus

كيف يجب أن يسأل الوكلاء أسئلة للتعلم المنشأ؟حوار مشروح كوربوس

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 Publication date 2021
and research's language is English
 Created by Shamra Editor




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Intelligent agents that are confronted with novel concepts in situated environments will need to ask their human teammates questions to learn about the physical world. To better understand this problem, we need data about asking questions in situated task-based interactions. To this end, we present the Human-Robot Dialogue Learning (HuRDL) Corpus - a novel dialogue corpus collected in an online interactive virtual environment in which human participants play the role of a robot performing a collaborative tool-organization task. We describe the corpus data and a corresponding annotation scheme to offer insight into the form and content of questions that humans ask to facilitate learning in a situated environment. We provide the corpus as an empirically-grounded resource for improving question generation in situated intelligent agents.



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