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. 2020 Mar 31;10:5732. doi: 10.1038/s41598-020-61994-0

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© The Author(s) 2020

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Conversational efficiency of AI agents. The x-axis represents the number of dialogue turns elapsed. The y-axis represents various performance metrics. Baseline refers to the performance of MCI classifier using all the responses generated from the original dataset. By contrast, RL refers to the performance of MCI classifier using responses generated by the user simulator, in response to the agent-generated questions at test time.